BibBase wild, s

2023 (12)

Optimization of Transformer Ratio and Beam Loading in a Plasma Wakefield Accelerator with a Structure-Exploiting Algorithm. Su, Q.; Larson, J.; Dalichaouch, T. N.; Li, F.; An, W.; Hildebrand, L.; Zhao, Y.; Decyk, V.; Alves, P.; Wild, S. M.; and Mori, W. B. Physics of Plasmas. 2023. To appear
doi link bibtex

@Article{PWFAOpt23,
  author      = {Su, Q. and Larson, J. and Dalichaouch, T. N. and Li, F. and An, W. and Hildebrand, L. and Zhao, Y. and Decyk, V. and Alves, P. and Wild, S. M. and Mori, W. B.},
  title       = {Optimization of Transformer Ratio and Beam Loading in a Plasma Wakefield Accelerator with a Structure-Exploiting Algorithm},
  doi         = {10.48550/ARXIV.2301.09697},
  note        = {To appear},
  anumber     = {2301.09697},
  aurl        = {https://arxiv.org/abs/2301.09697},
  institution = {arXiv},
  journal     = {Physics of Plasmas},
  year        = {2023},
}

Designing a Framework for Solving Multiobjective Simulation Optimization Problems. Chang, T. H.; and Wild, S. M. Technical Report 2304.06881, arXiv, 2023.

Designing a Framework for Solving Multiobjective Simulation Optimization Problems [link]

Paper link bibtex

@TechReport{ParMOODesign23,
  author      = {Tyler H. Chang and Stefan M. Wild},
  institution = {arXiv},
  title       = {Designing a Framework for Solving Multiobjective Simulation Optimization Problems},
  number      = {2304.06881},
  url         = {https://arxiv.org/abs/2304.06881},
  year        = {2023},
}

ParMOO: A Python Library for Parallel Multiobjective Simulation Optimization. Chang, T. H.; and Wild, S. M. Journal of Open Source Software, 8(82): 4468. 2023.
doi link bibtex

@Article{parmoo2023,
  author  = {Chang, Tyler H. and Wild, Stefan M.},
  title   = {{ParMOO}: A {P}ython Library for Parallel Multiobjective Simulation Optimization},
  doi     = {10.21105/joss.04468},
  number  = {82},
  pages   = {4468},
  volume  = {8},
  journal = {Journal of Open Source Software},
  year    = {2023},
}

Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization. Bollapragada, R.; and Wild, S. M. Mathematical Programming Computation. 2023. To appear

Adaptive Sampling Quasi-Newton Methods for Zeroth-Order Stochastic Optimization [link]

Paper doi link bibtex

@Article{RBSWlong21,
  author   = {Raghu Bollapragada and Stefan M. Wild},
  title    = {Adaptive Sampling Quasi-{N}ewton Methods for Zeroth-Order Stochastic Optimization},
  doi      = {10.1007/s12532-023-00233-9},
  note     = {To appear},
  url      = {https://arxiv.org/abs/2109.12213},
  anumber  = {2109.12213},
  anumber2 = {ANL/MCS-P9604-1021},
  journal  = {Mathematical Programming Computation},
  year     = {2023},
}

Constructing a Simulation Surrogate with Partially Observed Output. Chan, M. Y.; Plumlee, M.; and Wild, S. M. Technometrics. 2023. To appear

Constructing a Simulation Surrogate with Partially Observed Output [link]

Paper link bibtex

@Article{MCMPSW2022,
  author  = {Moses Y-H. Chan and Matthew Plumlee and Stefan M. Wild},
  title   = {Constructing a Simulation Surrogate with Partially Observed Output},
  note    = {To appear},
  url     = {http://arxiv.org/abs/2304.09372},
  anumber = {2304.09372},
  aurl    = {http://www.mcs.anl.gov/papers/P9634-1221.pdf},
  journal = {Technometrics},
  year    = {2023},
}

A Framework for Fully Autonomous Design of Materials via Multiobjective Optimization and Active Learning: Challenges and Next Steps. Chang, T. H.; Elias, J. R.; Wild, S. M.; Chaudhuri, S.; and Libera, J. A. In Workshop on ``Machine Learning for Materials'' ICLR 2023, 2023.

A Framework for Fully Autonomous Design of Materials via Multiobjective Optimization and Active Learning: Challenges and Next Steps [link]

Paper link bibtex

@InProceedings{ChangICLRW23,
  author    = {Tyler H. Chang and Jakob R. Elias and Stefan M. Wild and Santanu Chaudhuri and Joseph A. Libera},
  booktitle = {Workshop on ``Machine Learning for Materials'' ICLR 2023},
  title     = {A Framework for Fully Autonomous Design of Materials via Multiobjective Optimization and Active Learning: Challenges and Next Steps},
  url       = {https://openreview.net/forum?id=8KJS7RPjMqG},
  aurl      = {https://arxiv.org/abs/2304.07445},
  year      = {2023},
}

Bayesian Calibration of Viscous Anisotropic Hydrodynamic Simulations of Heavy-Ion Collisions. Liyanage, D.; Sürer, Ö.; Plumlee, M.; Wild, S. M.; and Heinz, U. Technical Report 2302.14184, arXiv, 2023.
doi link bibtex

@TechReport{LSPWH23,
  author      = {Liyanage, Dananjaya and S\"urer, \"Ozge and Plumlee, Matthew and Wild, Stefan M. and Heinz, Ulrich},
  institution = {arXiv},
  title       = {Bayesian Calibration of Viscous Anisotropic Hydrodynamic Simulations of Heavy-Ion Collisions},
  doi         = {10.48550/ARXIV.2302.14184},
  number      = {2302.14184},
  aurl        = {https://arxiv.org/abs/2302.14184},
  year        = {2023},
}

Optimization and Learning with Zeroth-order Stochastic Oracles. Wild, S. M. SIAM News, 56(1). 2023.

Optimization and Learning with Zeroth-order Stochastic Oracles [link]

Paper link bibtex

@Article{Wild23SN,
  author  = {Stefan M. Wild},
  title   = {Optimization and Learning with Zeroth-order Stochastic Oracles},
  number  = {1},
  url     = {https://sinews.siam.org/Details-Page/optimization-and-learning-with-zeroth-order-stochastic-oracles},
  volume  = {56},
  journal = {SIAM News},
  year    = {2023},
}

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers. Menickelly, M.; Wild, S. M.; and Xie, M. Technical Report 2302.09128, arXiv, 2023.
doi link bibtex

@TechReport{MMSWMX23,
  author      = {Matt Menickelly and Stefan M. Wild and Miaolan Xie},
  institution = {arXiv},
  title       = {A Stochastic Quasi-{Newton} Method in the Absence of Common Random Numbers},
  doi         = {10.48550/arXiv.2302.09128},
  number      = {2302.09128},
  aurl        = {https://arxiv.org/abs/2302.09128},
  year        = {2023},
}

Modeling Approaches for Addressing Simple Unrelaxable Constraints with Unconstrained Optimization Methods. Padidar, M.; Larson, J.; and Wild, S. M. Optimization Letters, 17: 561–589. 2023.
doi link bibtex

@Article{Padidar2022,
  author  = {Misha Padidar and Jeffrey Larson and Stefan M. Wild},
  title   = {Modeling Approaches for Addressing Simple Unrelaxable Constraints with Unconstrained Optimization Methods},
  doi     = {10.1007/s11590-022-01950-1},
  pages   = {561--589},
  volume  = {17},
  anumber = {2205.09627},
  journal = {Optimization Letters},
  year    = {2023},
}

Derivative-Free Optimization of a Rapid-Cycling Synchrotron. Eldred, J. S.; Larson, J.; Padidar, M.; Stern, E.; and Wild, S. M. Optimization and Engineering. 2023. To appear
doi link bibtex

@Article{Padidar2021,
  author  = {Jeffrey S. Eldred and Jeffrey Larson and Misha Padidar and Eric Stern and Stefan M. Wild},
  title   = {Derivative-Free Optimization of a Rapid-Cycling Synchrotron},
  doi     = {10.1007/s11081-022-09733-4},
  note    = {To appear},
  aurl    = {https://arxiv.org/abs/2108.04774},
  journal = {Optimization and Engineering},
  year    = {2023},
}

DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. Ćiprijanović, A.; Lewis, A.; Pedro, K.; Madireddy, S.; Nord, B.; Perdue, G. N.; and Wild, S. M. Machine Learning: Science and Technology, 4(2): 025013. 2023.
doi link bibtex

@Article{Ciprijanovic23,
  author  = {Aleksandra \'Ciprijanovi\'c and Ashia Lewis and Kevin Pedro and Sandeep Madireddy and Brian Nord and Gabriel Nathan Perdue and Stefan M.\ Wild},
  title   = {{DeepAstroUDA}: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection},
  doi     = {10.1088/2632-2153/acca5f},
  number  = {2},
  pages   = {025013},
  volume  = {4},
  anumber = {2302.02005},
  aurl    = {https://arxiv.org/abs/2302.02005},
  journal = {Machine Learning: Science and Technology},
  year    = {2023},
}

2022 (12)

Hashing-Like Johnson–Lindenstrauss Transforms and Their Extreme Singular Values. Dzahini, K. J.; and Wild, S. M. Technical Report 2212.14858, ArXiv, 2022.

Hashing-Like Johnson–Lindenstrauss Transforms and Their Extreme Singular Values [link]

Paper link bibtex

@TechReport{Dzahinihashing23,
  author      = {Kwassi Joseph Dzahini and Stefan M. Wild},
  institution = {ArXiv},
  title       = {Hashing-Like {Johnson--Lindenstrauss} Transforms and Their Extreme Singular Values},
  number      = {2212.14858},
  url         = {https://arxiv.org/abs/2212.14858},
  year        = {2022},
}

Numerical Evidence Against Advantage with Quantum Fidelity Kernels on Classical Data. Slattery, L.; Shaydulin, R.; Chakrabarti, S.; Pistoia, M.; Khairy, S.; and Wild, S. M. Technical Report 2211.16551, arXiv, 2022.

Numerical Evidence Against Advantage with Quantum Fidelity Kernels on Classical Data [link]

Paper link bibtex

@TechReport{Slattery22,
  author      = {Lucas Slattery and Ruslan Shaydulin and Shouvanik Chakrabarti and Marco Pistoia and Sami Khairy and Stefan M. Wild},
  institution = {arXiv},
  title       = {Numerical Evidence Against Advantage with Quantum Fidelity Kernels on Classical Data},
  number      = {2211.16551},
  url         = {https://arxiv.org/abs/2211.16551},
  year        = {2022},
}

libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations. Hudson, S.; Larson, J.; Navarro, J.; and Wild, S. M. IEEE Transactions on Parallel and Distributed Systems, 33(4): 977–988. 2022.
doi link bibtex

@Article{Hudson2022,
  author  = {Hudson, Stephen and Larson, Jeffrey and Navarro, John-Luke and Wild, Stefan M.},
  title   = {{libEnsemble: A} Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations},
  doi     = {10.1109/TPDS.2021.3082815},
  number  = {4},
  pages   = {977--988},
  volume  = {33},
  anumber = {ANL/MCS-P9447-0221},
  journal = {IEEE Transactions on Parallel and Distributed Systems},
  year    = {2022},
}

DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification. Ćiprijanović, A.; Kafkes, D.; Snyder, G.; Sánchez, F. J.; Perdue, G. N.; Pedro, K.; Nord, B.; Madireddy, S.; and Wild, S. M. Machine Learning: Science and Technology, 3(3): 035007. 2022.
doi link bibtex

@Article{Ciprijanovic21full,
  author      = {Aleksandra \'Ciprijanovi\'c and Diana Kafkes and Gregory Snyder and F. Javier S\'{a}nchez and Gabriel Nathan Perdue and Kevin Pedro and Brian Nord and Sandeep Madireddy and Stefan M.\ Wild},
  title       = {DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification},
  doi         = {10.1088/2632-2153/ac7f1a},
  number      = {3},
  pages       = {035007},
  volume      = {3},
  anumber     = {ANL/MCS-P9638-1221},
  arxivnumber = {2112.14299},
  journal     = {Machine Learning: Science and Technology},
  year        = {2022},
}

Uncertainty Quantification in Breakup Reactions. Sürer, Ö.; Nunes, F. M.; Plumlee, M.; and Wild, S. M. Physical Review C, 106: 024607. 2022.
doi link bibtex

@Article{SurerUQ22,
  author      = {\"Ozge S\"urer and Filomena M. Nunes and Matthew Plumlee and Stefan M. Wild},
  title       = {Uncertainty Quantification in Breakup Reactions},
  doi         = {10.1103/PhysRevC.106.024607},
  pages       = {024607},
  volume      = {106},
  anumber     = {P9589-0522},
  arxivnumber = {2205.07119},
  journal     = {Physical Review C},
  year        = {2022},
}

Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay: Project Scoping Workshop Report. Cirigliano, V.; Davoudi, Z.; Engel, J.; Furnstahl, R. J.; Hagen, G.; Heinz, U.; Hergert, H.; Horoi, M.; Johnson, C. W.; Lovato, A.; Mereghetti, E.; Nazarewicz, W.; Nicholson, A.; Papenbrock, T.; Pastore, S.; Plumlee, M.; Phillips, D. R.; Shanahan, P. E.; Stroberg, S. R.; Viens, F.; Walker-Loud, A.; Wendt, K. A.; and Wild, S. M. Technical Report 2207.01085, arXiv, 2022.
doi link bibtex

@TechReport{DBDReport2022,
  author      = {Cirigliano, V. and Davoudi, Z. and Engel, J. and Furnstahl, R. J. and Hagen, G. and Heinz, U. and Hergert, H. and Horoi, M. and Johnson, C. W. and Lovato, A. and Mereghetti, E. and Nazarewicz, W. and Nicholson, A. and Papenbrock, T. and Pastore, S. and Plumlee, M. and Phillips, D. R. and Shanahan, P. E. and Stroberg, S. R. and Viens, F. and Walker-Loud, A. and Wendt, K. A. and Wild, S. M.},
  institution = {arXiv},
  title       = {Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay: Project Scoping Workshop Report},
  doi         = {10.48550/ARXIV.2207.01085},
  number      = {2207.01085},
  year        = {2022},
}

Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay. Cirigliano, V.; Davoudi, Z.; Engel, J.; Furnstahl, R. J.; Hagen, G.; Heinz, U.; Hergert, H.; Horoi, M.; Johnson, C. W.; Lovato, A.; Mereghetti, E.; Nazarewicz, W.; Nicholson, A.; Papenbrock, T.; Pastore, S.; Plumlee, M.; Phillips, D. R.; Shanahan, P. E.; Stroberg, S. R.; Viens, F.; Walker-Loud, A.; Wendt, K. A.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 49(12): 120502. 2022.
doi link bibtex

@Article{DBDPaper2022,
  author  = {Cirigliano, V. and Davoudi, Z. and Engel, J. and Furnstahl, R. J. and Hagen, G. and Heinz, U. and Hergert, H. and Horoi, M. and Johnson, C. W. and Lovato, A. and Mereghetti, E. and Nazarewicz, W. and Nicholson, A. and Papenbrock, T. and Pastore, S. and Plumlee, M. and Phillips, D. R. and Shanahan, P. E. and Stroberg, S. R. and Viens, F. and Walker-Loud, A. and Wendt, K. A. and Wild, S. M.},
  title   = {Towards Precise and Accurate Calculations of Neutrinoless Double-Beta Decay},
  doi     = {10.1088/1361-6471/aca03e},
  number  = {12},
  pages   = {120502},
  volume  = {49},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  year    = {2022},
}

Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. Ćiprijanović, A.; Lewis, A.; Pedro, K.; Madireddy, S.; Nord, B.; Perdue, G. N.; and Wild, S. M. In Machine Learning and the Physical Sciences – NeurIPS Workshop, 2022.
doi link bibtex

@InProceedings{Ciprijanovic22workshop,
  author    = {Aleksandra \'Ciprijanovi\'c and Ashia Lewis and Kevin Pedro and Sandeep Madireddy and Brian Nord and Gabriel Nathan Perdue and Stefan M.\ Wild},
  booktitle = {Machine Learning and the Physical Sciences -- NeurIPS Workshop},
  title     = {Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection},
  doi       = {10.48550/ARXIV.2211.00677},
  anumber   = {2211.00677},
  aurl      = {https://arxiv.org/abs/2211.00677},
  year      = {2022},
}

Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses. Dzahini, K. J.; and Wild, S. M. Technical Report 2207.06452, ArXiv, 2022.

Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses [link]

Paper link bibtex

@TechReport{STARS2022,
  author      = {Kwassi Joseph Dzahini and Stefan M. Wild},
  institution = {ArXiv},
  title       = {Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses},
  number      = {2207.06452},
  url         = {https://arxiv.org/abs/2207.06452},
  year        = {2022},
}

Stochastic Average Model Methods. Menickelly, M.; and Wild, S. M. Technical Report 2207.06305, ArXiv, 2022.

Paper link bibtex

@TechReport{SAMP2022,
  author      = {Matt Menickelly and Stefan M. Wild},
  institution = {ArXiv},
  title       = {Stochastic Average Model Methods},
  number      = {2207.06305},
  url         = {https://arxiv.org/abs/2207.06305},
  year        = {2022},
}

Importance of Kernel Bandwidth in Quantum Machine Learning. Shaydulin, R.; and Wild, S. M. Physical Review A, 106(4): 042407. 2022.
doi link bibtex

@Article{RSSW21,
  author  = {Ruslan Shaydulin and Stefan M. Wild},
  title   = {Importance of Kernel Bandwidth in Quantum Machine Learning},
  doi     = {10.1103/PhysRevA.106.042407},
  number  = {4},
  pages   = {042407},
  volume  = {106},
  aurl    = {https://arxiv.org/abs/2111.05451},
  journal = {Physical Review A},
  year    = {2022},
}

Bandwidth Enables Generalization in Quantum Kernel Models. Canatar, A.; Peters, E.; Pehlevan, C.; Wild, S. M.; and Shaydulin, R. Technical Report 2206.06686, arXiv, 2022.

Bandwidth Enables Generalization in Quantum Kernel Models [link]

Paper doi link bibtex

@TechReport{Bandwidth2022,
  author      = {Canatar, Abdulkadir and Peters, Evan and Pehlevan, Cengiz and Wild, Stefan M. and Shaydulin, Ruslan},
  institution = {arXiv},
  title       = {Bandwidth Enables Generalization in Quantum Kernel Models},
  doi         = {10.48550/ARXIV.2206.06686},
  number      = {2206.06686},
  url         = {https://arxiv.org/abs/2206.06686},
  year        = {2022},
}

2021 (13)

A Method for Convex Black-Box Integer Global Optimization. Larson, J.; Leyffer, S.; Palkar, P.; and Wild, S. M. Journal of Global Optimization, 80: 439–477. 2021.
doi link bibtex

@Article{Palkar2019,
  author  = {Jeffrey Larson and Sven Leyffer and Prashant Palkar and Stefan M. Wild},
  title   = {A Method for Convex Black-Box Integer Global Optimization},
  doi     = {10.1007/s10898-020-00978-w},
  pages   = {439--477},
  volume  = {80},
  anumber = {1903.11366},
  aurl    = {https://arxiv.org/abs/1903.11366},
  gurl    = {https://scholar.google.com/scholar?cluster=7575868501545742847},
  journal = {Journal of Global Optimization},
  year    = {2021},
}

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis. Brown, J.; He, Y.; MacLachlan, S.; Menickelly, M.; and Wild, S. M. SIAM Journal on Scientific Computing, 43(1): A109–A138. 2021.
doi link bibtex

@Article{BHMMW20,
  author  = {Jed Brown and Yunhui He and Scott {MacLachlan} and Matt Menickelly and Stefan M. Wild},
  title   = {Tuning Multigrid Methods with Robust Optimization and Local {Fourier} Analysis},
  doi     = {10.1137/19m1308669},
  number  = {1},
  pages   = {A109--A138},
  volume  = {43},
  anumber = {ANL/MCS-9272-0120},
  aurl    = {https://arxiv.org/abs/2001.00887},
  journal = {SIAM Journal on Scientific Computing},
  year    = {2021},
}

Scalable Statistical Inference of Photometric Redshift via Data Subsampling. Fadikar, A.; Wild, S. M.; and Chaves-Montero, J. In Computational Science – ICCS 2021, pages 245–258, 2021. Springer
doi link bibtex

@InProceedings{FadikarRedshift2021,
  author    = {Arindam Fadikar and Stefan M. Wild and Jonas Chaves-Montero},
  booktitle = {Computational Science -- ICCS 2021},
  title     = {Scalable Statistical Inference of Photometric Redshift via Data Subsampling},
  doi       = {10.1007/978-3-030-77977-1_19},
  pages     = {245--258},
  publisher = {Springer},
  year      = {2021},
}

Get on the BAND Wagon: A Bayesian Framework for Quantifying Model Uncertainties in Nuclear Dynamics. Phillips, D. R.; Furnstahl, R. J.; Heinz, U.; Maiti, T.; Nazarewicz, W.; Nunes, F. M.; Plumlee, M.; Pratola, M. T.; Pratt, S.; Viens, F. G.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 48(7): 072001. 2021.
doi link bibtex

@Article{BANDwagon21,
  author   = {Daniel R. Phillips and Richard J. Furnstahl and Ulrich Heinz and Tapabrata Maiti and Witold Nazarewicz and Filomena M. Nunes and Matthew Plumlee and Matthew T. Pratola and Scott Pratt and Frederi G. Viens and Stefan M. Wild},
  title    = {Get on the {BAND} Wagon: A {Bayesian} Framework for Quantifying Model Uncertainties in Nuclear Dynamics},
  doi      = {10.1088/1361-6471/abf1df},
  number   = {7},
  pages    = {072001},
  volume   = {48},
  aanumber = {2012.07704},
  anumber  = {ANL/MCS-P9443-0212},
  journal  = {Journal of Physics G: Nuclear and Particle Physics},
  year     = {2021},
}

Hierarchical Analysis of Halo Center in Cosmology. Di, Z. W.; Rangel, E.; Yoo, S.; and Wild, S. M. In Computational Science – ICCS 2021, pages 671–684, 2021. Springer
doi link bibtex

@InProceedings{DiHalo2021,
  author    = {Zichao Wendy Di and Esteban Rangel and Shinjae Yoo and Stefan M. Wild},
  booktitle = {Computational Science -- ICCS 2021},
  title     = {Hierarchical Analysis of Halo Center in Cosmology},
  doi       = {10.1007/978-3-030-77961-0_53},
  pages     = {671--684},
  publisher = {Springer},
  year      = {2021},
}

Machine Learning-Based Inversion of Nuclear Responses. Raghavan, K.; Balaprakash, P.; Lovato, A.; Rocco, N.; and Wild, S. M. Physical Review C, 103(3): 035502. 2021.
doi link bibtex

@Article{Euclidinverse21,
  author  = {Krishnan Raghavan and Prasanna Balaprakash and Alessandro Lovato and Noemi Rocco and Stefan M. Wild},
  title   = {Machine Learning-Based Inversion of Nuclear Responses},
  doi     = {10.1103/physrevc.103.035502},
  number  = {3},
  pages   = {035502},
  volume  = {103},
  anumber = {2010.12703},
  journal = {Physical Review C},
  year    = {2021},
}

Randomized Algorithms for Scientific Computing. Buluc, A.; Kolda, T. G.; Wild, S. M.; Anitescu, M.; DeGennaro, A.; Jakeman, J.; Kamath, C.; Ramakrishnan; Kannan; Lopes, M. E.; Martinsson, P.; Myers, K.; Nelson, J.; Restrepo, J. M.; Seshadhri, C.; Vrabie, D.; Wohlberg, B.; Wright, S. J.; Yang, C.; and Zwart, P. Technical Report U.S.\ Department of Energy, ASCR, 2021.
doi link bibtex

@TechReport{RASC2021,
  author      = {Aydin Buluc and Tamara G. Kolda and Stefan M. Wild and Mihai Anitescu and Anthony {DeGennaro} and John Jakeman and Chandrika Kamath and Ramakrishnan and Kannan and Miles E. Lopes and Per-Gunnar Martinsson and Kary Myers and Jelani Nelson and Juan M. Restrepo and C. Seshadhri and Draguna Vrabie and Brendt Wohlberg and Stephen J. Wright and Chao Yang and Peter Zwart},
  institution = {U.S.\ Department of Energy, ASCR},
  title       = {Randomized Algorithms for Scientific Computing},
  doi         = {10.2172/1807223},
  type        = {Report},
  arxivnumber = {2104.11079},
  publisher   = {Office of Scientific and Technical Information},
  year        = {2021},
}

Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control. Renganathan, S. A.; Larson, J.; and Wild, S. M. Technical Report 2105.09824, ArXiv, 2021.

Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control [link]

Paper link bibtex

@TechReport{Renganathan2021,
  author      = {S. Ashwin Renganathan and Jeffrey Larson and Stefan M. Wild},
  institution = {ArXiv},
  title       = {Lookahead Acquisition Functions for Finite-Horizon Time-Dependent {Bayesian} Optimization and Application to Quantum Optimal Control},
  number      = {2105.09824},
  url         = {https://arxiv.org/abs/2105.09824},
  year        = {2021},
}

Robustness of Deep Learning Algorithms in Astronomy – Galaxy Morphology Studies. Ćiprijanović, A.; Kafkes, D.; Perdue, G. N.; Pedro, K.; Snyder, G.; Sánchez, F. J.; Madireddy, S.; Wild, S. M.; and Nord, B. In Machine Learning and the Physical Sciences – NeurIPS Workshop, 2021.

Robustness of Deep Learning Algorithms in Astronomy – Galaxy Morphology Studies [link]

Paper link bibtex

@InProceedings{Ciprijanovic21workshop,
  author    = {Aleksandra \'Ciprijanovi\'c and Diana Kafkes and Gabriel Nathan Perdue and Kevin Pedro and Gregory Snyder and F. Javier S\'{a}nchez and Sandeep Madireddy and Stefan M.\ Wild and Brian Nord},
  booktitle = {Machine Learning and the Physical Sciences -- NeurIPS Workshop},
  title     = {Robustness of Deep Learning Algorithms in Astronomy -- Galaxy Morphology Studies},
  url       = {https://arxiv.org/abs/2111.00961},
  aanumber  = {ANL/MCS-P9639-1221},
  anumber   = {2111.00961},
  aurl      = {https://ml4physicalsciences.github.io/2021/files/NeurIPS_ML4PS_2021_6.pdf},
  year      = {2021},
}

Sequential Learning of Active Subspaces. Wycoff, N.; Binois, M.; and Wild, S. M. Journal of Computational and Graphical Statistics, 30(4): 1224–1237. 2021.
doi link bibtex

@Article{Wycoff2021,
  author  = {Nathan Wycoff and Micka\"el Binois and Stefan M. Wild},
  title   = {Sequential Learning of Active Subspaces},
  doi     = {10.1080/10618600.2021.1874962},
  number  = {4},
  pages   = {1224--1237},
  volume  = {30},
  anumber = {ANL/MCS-P9196-0719},
  aurl    = {https://arxiv.org/abs/1907.11572},
  journal = {Journal of Computational and Graphical Statistics},
  year    = {2021},
}

Exploiting Symmetry Reduces the Cost of Training QAOA. Shaydulin, R.; and Wild, S. M. IEEE Transactions on Quantum Engineering, 2: 1–9. 2021.
doi link bibtex

@Article{RSSMW21a,
  author  = {Ruslan Shaydulin and Stefan M. Wild},
  title   = {Exploiting Symmetry Reduces the Cost of Training {QAOA}},
  doi     = {10.1109/TQE.2021.3066275},
  pages   = {1--9},
  volume  = {2},
  anumber = {2101.10296},
  journal = {IEEE Transactions on Quantum Engineering},
  year    = {2021},
}

The Middle Science: Traversing Scale in Complex Many-Body Systems. Clark, A. E.; Adams, H.; Hernandez, R.; Krylov, A. I.; Niklasson, A. M. N.; Sarupria, S.; Wang, Y.; Wild, S. M.; and Yang, Q. ACS Central Science, 7(8): 1271–1287. 2021.
doi link bibtex

@Article{MiddleScience2021,
  author    = {Aurora E. Clark and Henry Adams and Rigoberto Hernandez and Anna I. Krylov and Anders M. N. Niklasson and Sapna Sarupria and Yusu Wang and Stefan M. Wild and Qian Yang},
  title     = {The Middle Science: Traversing Scale in Complex Many-Body Systems},
  doi       = {10.1021/acscentsci.1c00685},
  number    = {8},
  pages     = {1271--1287},
  volume    = {7},
  journal   = {{ACS} Central Science},
  publisher = {American Chemical Society},
  year      = {2021},
}

Optimization and Supervised Machine Learning Methods for Fitting Numerical Physics Models without Derivatives. Bollapragada, R.; Menickelly, M.; Nazarewicz, W.; O'Neal, J.; Reinhard, P.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 48(2): 024001. 2021.
doi link bibtex

@Article{BMNORW2020,
  author  = {Raghu Bollapragada and Matt Menickelly and Witold Nazarewicz and Jared O'Neal and Paul-Gerhard Reinhard and Stefan M. Wild},
  title   = {Optimization and Supervised Machine Learning Methods for Fitting Numerical Physics Models without Derivatives},
  doi     = {10.1088/1361-6471/abd009},
  number  = {2},
  pages   = {024001},
  volume  = {48},
  aurl    = {https://arxiv.org/abs/2010.05668},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  year    = {2021},
}

2020 (6)

Derivative-Free Robust Optimization by Outer Approximations. Menickelly, M.; and Wild, S. M. Mathematical Programming, 179(1–2): 157–193. 2020.
doi link bibtex

@Article{MMSMW2017,
  author  = {Matt Menickelly and Stefan M. Wild},
  title   = {Derivative-Free Robust Optimization by Outer Approximations},
  doi     = {10.1007/s10107-018-1326-9},
  number  = {1--2},
  pages   = {157--193},
  volume  = {179},
  aurl    = {http://www.mcs.anl.gov/papers/P9004-1017.pdf},
  gurl    = {https://scholar.google.com/scholar?cluster=18181496191524112742},
  journal = {Mathematical Programming},
  year    = {2020},
}

A Survey of Nonlinear Robust Optimization. Leyffer, S.; Menickelly, M.; Munson, T.; Vanaret, C.; and Wild, S. M. INFOR: Information Systems and Operational Research, 58(2): 342–373. 2020.
doi link bibtex

@Article{NROSurvey2018,
  author  = {Sven Leyffer and Matt Menickelly and Todd Munson and Charlie Vanaret and Stefan M. Wild},
  title   = {A Survey of Nonlinear Robust Optimization},
  doi     = {10.1080/03155986.2020.1730676},
  number  = {2},
  pages   = {342--373},
  volume  = {58},
  anumber = {ANL/MCS-P9040-0218},
  aurl    = {http://www.mcs.anl.gov/papers/P9040-0218.pdf},
  journal = {INFOR: Information Systems and Operational Research},
  year    = {2020},
}

Calibration of Energy Density Functionals with Deformed Nuclei. Schunck, N.; O'Neal, J.; Grosskopf, M.; Lawrence, E.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 47(7): 074001. 2020.
doi link bibtex

@Article{SOGLW20,
  author  = {Nicolas Schunck and Jared O'Neal and Michael Grosskopf and Earl Lawrence and Stefan M. Wild},
  title   = {Calibration of Energy Density Functionals with Deformed Nuclei},
  doi     = {10.1088/1361-6471/ab8745},
  number  = {7},
  pages   = {074001},
  volume  = {47},
  anumber = {ANL/MCS-P9283-0220},
  aurl    = {https://arxiv.org/abs/2003.12207},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  year    = {2020},
}

Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications. Cheriere, N.; Dorier, M.; Antoniu, G.; Wild, S. M.; Leyffer, S.; and Ross, R. In 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2020), 2020.
doi link bibtex

@InProceedings{Cheriere2020,
  author    = {Nathanael Cheriere and Matthieu Dorier and Gabriel Antoniu and Stefan M. Wild and Sven Leyffer and Robert Ross},
  booktitle = {20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2020)},
  title     = {Pufferscale: Rescaling {HPC} Data Services for High Energy Physics Applications},
  doi       = {10.1109/ccgrid49817.2020.00-75},
  year      = {2020},
}

Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization. Renganathan, S. A.; Larson, J.; and Wild, S. M. Technical Report 2006.08037, ArXiv, 2020.

Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization [link]

Paper link bibtex

@TechReport{Renganathan2020,
  author      = {S. Ashwin Renganathan and Jeffrey Larson and Stefan M. Wild},
  institution = {ArXiv},
  title       = {Recursive Two-Step Lookahead Expected Payoff for Time-Dependent {Bayesian} Optimization},
  number      = {2006.08037},
  url         = {https://arxiv.org/abs/2006.08037},
  year        = {2020},
}

Looking Ahead to the 2021 SIAM Conference on Computational Science and Engineering. Grigori, L.; Kilmer, M.; and Wild, S. M. SIAM News, 53(4). 2020.

Looking Ahead to the 2021 SIAM Conference on Computational Science and Engineering [pdf]

2

Looking Ahead to the 2021 SIAM Conference on Computational Science and Engineering [link]

Paper link bibtex

@Article{CSE21SN,
  author  = {Laura Grigori and Misha Kilmer and Stefan M. Wild},
  title   = {Looking Ahead to the 2021 {SIAM Conference on Computational Science and Engineering}},
  number  = {4},
  url     = {https://sinews.siam.org/Details-Page/looking-ahead-to-the-2021-siam-conference-on-computational-science-and-engineering},
  volume  = {53},
  journal = {SIAM News},
  url2    = {https://sinews.siam.org/Portals/Sinews2/Issue%20Pdfs/sn_May2020.pdf},
  year    = {2020},
}

2019 (10)

Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. Balaprakash, P.; Egele, R.; Salim, M.; Vishwanath, V.; Wild, S. M.; Xia, F.; Brettin, T.; and Stevens, R. In International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), pages 37:1–37:33, 2019. ACM
doi link bibtex

@InProceedings{Balapra-NAS2019,
  author    = {Prasanna Balaprakash and Romain Egele and Misha Salim and Venkatram Vishwanath and Stefan M. Wild and Fangfang Xia and Tom Brettin and Rick Stevens},
  booktitle = {International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19)},
  title     = {Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research},
  doi       = {10.1145/3295500.3356202},
  pages     = {37:1--37:33},
  publisher = {ACM},
  anumber   = {1909.00311},
  year      = {2019},
}

Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence. Baker, N.; Alexander, F.; Bremer, T.; Hagberg, A.; Kevrekidis, Y.; Najm, H.; Parashar, M.; Patra, A.; Sethian, J.; Wild, S. M.; and Willcox, K. Technical Report U.S.\ Department of Energy, ASCR, 2019.
doi link bibtex

@TechReport{Baker2019,
  author      = {Nathan Baker and Frank Alexander and Timo Bremer and Aric Hagberg and Yannis Kevrekidis and Habib Najm and Manish Parashar and Abani Patra and James Sethian and Stefan M. Wild and Karen Willcox},
  institution = {U.S.\ Department of Energy, ASCR},
  title       = {Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence},
  doi         = {10.2172/1478744},
  type        = {Report},
  publisher   = {Office of Scientific and Technical Information},
  year        = {2019},
}

Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach. Austin, A.; Di, Z. W.; Leyffer, S.; and Wild, S. M. SIAM Journal on Scientific Computing, 41(3): B497–B521. 2019.
doi link bibtex

@Article{ADLW19,
  author  = {Anthony Austin and Zichao Wendy Di and Sven Leyffer and Stefan M. Wild},
  title   = {Simultaneous Sensing Error Recovery and Tomographic Inversion Using an Optimization-Based Approach},
  doi     = {10.1137/18M121993X},
  number  = {3},
  pages   = {B497--B521},
  volume  = {41},
  anumber = {ANL/MCS-P9136-0918},
  aurl    = {https://arxiv.org/abs/1902.02027},
  journal = {SIAM Journal on Scientific Computing},
  year    = {2019},
}

Derivative-Free Optimization Methods. Larson, J.; Menickelly, M.; and Wild, S. M. Acta Numerica, 28: 287–404. 2019.
doi link bibtex

@Article{LMW2019AN,
  author  = {Jeffrey Larson and Matt Menickelly and Stefan M. Wild},
  title   = {Derivative-Free Optimization Methods},
  doi     = {10.1017/s0962492919000060},
  pages   = {287--404},
  volume  = {28},
  journal = {Acta Numerica},
  year    = {2019},
}

libEnsemble User Manual, Version 0.5.2. Hudson, S.; Larson, J.; Wild, S. M.; Bindel, D.; and Navarro, J. Technical Report Argonne National Laboratory, 2019.

libEnsemble User Manual, Version 0.5.2 [link]

Paper link bibtex

@TechReport{libensemble-man,
  author      = {Stephen Hudson and Jeffrey Larson and Stefan M. Wild and David Bindel and John-Luke Navarro},
  institution = {Argonne National Laboratory},
  title       = {{libEnsemble} User Manual, Version 0.5.2},
  type        = {Tech report},
  url         = {https://libensemble.readthedocs.io},
  anumber     = {ANL/MCS-TM-XXX},
  year        = {2019},
}

Adaptive Sampling Quasi-Newton Methods for Derivative-Free Stochastic Optimization. Bollapragada, R.; and Wild, S. M. In Beyond First Order Methods in Machine Learning NeurIPS 2019 Workshop, 2019.

Adaptive Sampling Quasi-Newton Methods for Derivative-Free Stochastic Optimization [link]

Paper link bibtex

@InProceedings{RBSWshort19,
  author    = {Raghu Bollapragada and Stefan M. Wild},
  booktitle = {Beyond First Order Methods in Machine Learning NeurIPS 2019 Workshop},
  title     = {Adaptive Sampling Quasi-{N}ewton Methods for Derivative-Free Stochastic Optimization},
  url       = {https://sites.google.com/site/optneurips19/},
  aaurl     = {https://arxiv.org/abs/1910.13516},
  anumber   = {1910.13516},
  mcsnumber = {ANL/MCS-P9236-0919},
  year      = {2019},
}

Optimization-Based Simultaneous Alignment and Reconstruction in Fluorescence Tomography. Di, Z. W.; Chen, S.; Gursoy, D.; Paunesku, T.; Leyffer, S.; Wild, S. M.; and Vogt, S. Optics Letters, 44(17): 4331–4334. 2019.
doi link bibtex

@Article{Di19,
  author  = {Zichao Wendy Di and Si Chen and Doga Gursoy and Tatjana Paunesku and Sven Leyffer and Stefan M.\ Wild and Stefan Vogt},
  title   = {Optimization-Based Simultaneous Alignment and Reconstruction in Fluorescence Tomography},
  doi     = {10.1364/OL.44.004331},
  number  = {17},
  pages   = {4331--4334},
  volume  = {44},
  journal = {Optics Letters},
  year    = {2019},
}

Large Area Imaging of Integrated Circuits Using Hard X-Ray Ptychography. Klug, J.; Deng, J.; Jiang, Y.; Preissner, C.; Di, Z. W.; Bicer, T.; Wild, S. M.; Vogt, S.; Sandberg, R.; and Honig, S. Technical Report 17-2, Argonne, 2019.
link bibtex

@TechReport{Klug2019,
  author      = {Jeffrey Klug and Junjing Deng and Yi Jiang and Curt Preissner and Zichao Wendy Di and Tekin Bicer and Stefan M. Wild and Stefan Vogt and Richard Sandberg and Steven Honig},
  institution = {Argonne},
  title       = {Large Area Imaging of Integrated Circuits Using Hard {X}-Ray Ptychography},
  number      = {17-2},
  aurl        = {https://www.gomactech.net/2019/},
  year        = {2019},
}

Calibrating Sensing Drift in Tomographic Inversion. Huang, X.; Di, Z. W.; and Wild, S. M. In 2019 IEEE International Conference on Image Processing (ICIP19), pages 1267–1271, 2019.
doi link bibtex

@InProceedings{Huang19a,
  author    = {Xiang Huang and Zichao Wendy Di and Stefan M. Wild},
  booktitle = {2019 IEEE International Conference on Image Processing (ICIP19)},
  title     = {Calibrating Sensing Drift in Tomographic Inversion},
  doi       = {10.1109/ICIP.2019.8803744},
  pages     = {1267--1271},
  anumber   = {ANL/MCS-P9159-0119},
  aurl      = {http://www.mcs.anl.gov/papers/P9159-0119.pdf},
  year      = {2019},
}

Adaptive Learning for Concept Drift in Application Performance Modeling. Madireddy, S.; Balaprakash, P.; Carns, P.; Latham, R.; Lockwood, G.; Ross, R.; Snyder, S.; and Wild, S. M. In Proceedings of the 48th International Conference on Parallel Processing (ICPP 2019), pages 79:1–79:11, 2019.
doi link bibtex

@InProceedings{Madireddy18a,
  author    = {Sandeep Madireddy and Prasanna Balaprakash and Philip Carns and Robert Latham and Glenn Lockwood and Robert Ross and Shane Snyder and Stefan M. Wild},
  booktitle = {Proceedings of the 48th International Conference on Parallel Processing (ICPP 2019)},
  title     = {Adaptive Learning for Concept Drift in Application Performance Modeling},
  doi       = {10.1145/3337821.3337922},
  pages     = {79:1--79:11},
  anumber   = {ANL/MCS-P9132-0918},
  aurl      = {http://www.mcs.anl.gov/papers/P9132-0918.pdf},
  year      = {2019},
}

2018 (10)

3D X-Ray Imaging of Continuous Objects beyond the Depth of Focus Limit. Gilles, M. A. T.; Nashed, Y. S. G.; Du, M.; Jacobsen, C.; and Wild, S. M. Optica, 5(9): 1078–1086. 2018.
doi link bibtex

@Article{Gilles18app,
  author  = {Marc Aurele T. Gilles and Youssef S. G. Nashed and Ming Du and Chris Jacobsen and Stefan M. Wild},
  title   = {{3D} X-Ray Imaging of Continuous Objects beyond the Depth of Focus Limit},
  doi     = {10.1364/OPTICA.5.001078},
  number  = {9},
  pages   = {1078--1086},
  volume  = {5},
  anumber = {ANL/MCS-P9062-0418},
  journal = {Optica},
  year    = {2018},
}

Doing Moore with Less – Leapfrogging Moore's Law with Inexactness for Supercomputing. Leyffer, S.; Wild, S. M.; Fagan, M.; Snir, M.; Palem, K.; Finkel, H.; and Yoshii, K. In 3rd International Workshop on Post-Moore Era Supercomputing (PMES), of SC18 Workshops, 2018.

Doing Moore with Less – Leapfrogging Moore's Law with Inexactness for Supercomputing [link]

Paper link bibtex

@InProceedings{PMES18,
  author    = {Sven Leyffer and Stefan M. Wild and Mike Fagan and Marc Snir and Krishna Palem and Hal Finkel and Kazutomo Yoshii},
  booktitle = {3rd International Workshop on Post-Moore Era Supercomputing (PMES)},
  title     = {Doing {Moore} with Less -- Leapfrogging {Moore's} Law with Inexactness for Supercomputing},
  series    = {SC18 Workshops},
  url       = {https://sites.google.com/view/pmes18/home},
  anumber   = {ANL/MCS-PXXXX-0918},
  year      = {2018},
}

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks. Balaprakash, P.; Salim, M.; Uram, T. D.; Vishwanath, V.; and Wild, S. M. In 25th IEEE International Conference on High Performance Computing (HiPC18), 2018.
doi link bibtex

@InProceedings{DeepHyper18,
  author    = {Prasanna Balaprakash and Michael Salim and Thomas D. Uram and Venkat Vishwanath and Stefan M. Wild},
  booktitle = {25th IEEE International Conference on High Performance Computing (HiPC18)},
  title     = {{DeepHyper}: Asynchronous Hyperparameter Search for Deep Neural Networks},
  doi       = {10.1109/hipc.2018.00014},
  anumber   = {ANL/MCS-PXXXX-0618},
  gurl      = {https://scholar.google.com/scholar?hl=en&as_sdt=0%2C14&q=DeepHyper%3A+Asynchronous+Hyperparameter+Search+for+Deep+Neural+Networks&btnG=},
  year      = {2018},
}

Robust Learning of Trimmed Estimators via Manifold Sampling. Menickelly, M.; and Wild, S. M. In Modern Trends in Nonconvex Optimization for Machine Learning – ICML 2018 Workshop, 2018.

Robust Learning of Trimmed Estimators via Manifold Sampling [link]

Paper link bibtex

@InProceedings{MMSMW2018,
  author    = {Matt Menickelly and Stefan M. Wild},
  booktitle = {Modern Trends in Nonconvex Optimization for Machine Learning -- ICML 2018 Workshop},
  title     = {Robust Learning of Trimmed Estimators via Manifold Sampling},
  url       = {https://sites.google.com/view/icml2018nonconvex/papers},
  aaurl     = {https://arxiv.org/abs/1807.02736},
  anumber   = {ANL/MCS-P9074-0618},
  aurl      = {http://www.mcs.anl.gov/papers/P9074-0618.pdf},
  axnumber  = {1807.02736},
  year      = {2018},
}

Accurate, Rapid Identification of Dislocation Lines in Coherent Diffractive Imaging via a Min-Max Optimization Formulation. Ulvestad, A.; Menickelly, M.; and Wild, S. M. AIP Advances, 8(1): 015114. 2018.
doi link bibtex

@Article{Ulvestad18,
  author  = {Andrew Ulvestad and Matt Menickelly and Stefan M. Wild},
  title   = {Accurate, Rapid Identification of Dislocation Lines in Coherent Diffractive Imaging via a Min-Max Optimization Formulation},
  doi     = {10.1063/1.5017596},
  number  = {1},
  pages   = {015114},
  volume  = {8},
  anumber = {ANL/MCS-P9030-1117},
  aurl    = {http://www.mcs.anl.gov/uploads/cels/papers/P9030-1117.pdf},
  journal = {{AIP} Advances},
  year    = {2018},
}

Modeling I/O Performance Variability Using Conditional Variational Auto Encoders. Madireddy, S.; Balaprakash, P.; Carns, P.; Latham, R.; Ross, R.; Snyder, S.; and Wild, S. M. In IEEE Cluster Conference, pages 109–113, 2018.
doi link bibtex

@InProceedings{Madireddy18,
  author      = {Sandeep Madireddy and Prasanna Balaprakash and Philip Carns and Robert Latham and Robert Ross and Shane Snyder and Stefan M. Wild},
  booktitle   = {IEEE Cluster Conference},
  title       = {Modeling {I/O} Performance Variability Using Conditional Variational Auto Encoders},
  doi         = {10.1109/CLUSTER.2018.00022},
  pages       = {109--113},
  anumber     = {ANL/MCS-P9070-0518},
  aurl        = {http://www.mcs.anl.gov/papers/PXXX-0518.pdf},
  institution = {Argonne National Laboratory, MCS Division},
  year        = {2018},
}

Understanding and Improving the Trust in Results of Numerical Simulations and Scientific Data Analytics. Cappello, F.; Gupta, R.; Di, S.; Constantinescu, E. M.; Peterka, T.; and Wild, S. M. In Euro-Par 2017: Parallel Processing Workshops, pages 545–556, 2018. Springer
doi link bibtex

@InProceedings{Cappello2017ep,
  author    = {Cappello, Franck and Gupta, Rinku and Di, Sheng and Constantinescu, Emil M. and Peterka, Tom and Wild, Stefan M.},
  booktitle = {Euro-Par 2017: Parallel Processing Workshops},
  title     = {Understanding and Improving the Trust in Results of Numerical Simulations and Scientific Data Analytics},
  doi       = {10.1007/978-3-319-75178-8_44},
  pages     = {545--556},
  publisher = {Springer},
  anote     = {see ANL/MCS-TM-352},
  aurl      = {http://www.mcs.anl.gov/papers/ANL/MCS-TM-352.pdf},
  year      = {2018},
}

Asynchronously Parallel Optimization Solver for Finding Multiple Minima. Larson, J.; and Wild, S. M. Mathematical Programming Computation, 10(3): 303–332. 2018.
doi link bibtex

@Article{LW16,
  author  = {Jeffrey Larson and Stefan M. Wild},
  title   = {Asynchronously Parallel Optimization Solver for Finding Multiple Minima},
  doi     = {10.1007/s12532-017-0131-4},
  number  = {3},
  pages   = {303--332},
  volume  = {10},
  anumber = {ANL/MCS-P5575-0316},
  gurl    = {https://scholar.google.com/scholar?cluster=16597238545742984308},
  journal = {Mathematical Programming Computation},
  year    = {2018},
}

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems. Madireddy, S.; Balaprakash, P.; Carns, P.; Latham, R.; Ross, R.; Snyder, S.; and Wild, S. M. In Lecture Notes in Computer Science: ISC High Performance 2018: High Performance Computing, pages 184–204, 2018. Springer
doi link bibtex

@InProceedings{Madireddy17b,
  author    = {Sandeep Madireddy and Prasanna Balaprakash and Philip Carns and Robert Latham and Robert Ross and Shane Snyder and Stefan M. Wild},
  booktitle = {Lecture Notes in Computer Science: ISC High Performance 2018: High Performance Computing},
  title     = {Machine Learning Based Parallel {I/O} Predictive Modeling: A Case Study on {Lustre} File Systems},
  doi       = {10.1007/978-3-319-92040-5_10},
  pages     = {184--204},
  publisher = {Springer},
  anumber   = {ANL/MCS-P9021-1017},
  aurl      = {http://www.mcs.anl.gov/papers/P9021-1017.pdf},
  year      = {2018},
}

Manifold Sampling for Optimization of Nonconvex Functions that are Piecewise Linear Compositions of Smooth Components. Khan, K. A.; Larson, J.; and Wild, S. M. SIAM Journal on Optimization, 28(4): 3001–3024. 2018.
doi link bibtex

@Article{KLW18,
  author  = {Kamil A. Khan and Jeffrey Larson and Stefan M. Wild},
  title   = {Manifold Sampling for Optimization of Nonconvex Functions that are Piecewise Linear Compositions of Smooth Components},
  doi     = {10.1137/17m114741x},
  number  = {4},
  pages   = {3001--3024},
  volume  = {28},
  gurl    = {https://scholar.google.com/scholar?cluster=2794324476499547388},
  journal = {{SIAM} Journal on Optimization},
  year    = {2018},
}

2017 (9)

Advancing Cross-Cutting Ideas for Computational Climate Science. Evans, K.; Ng, E. G.; Caldwell, P.; Hoffman, F. M.; Jackson, C.; Kleese van Dam, K.; Leung, L.; Martin, D.; Ostrouchov, G.; Tuminaro, R.; Ullrich, P.; Wild, S. M.; and Williams, S. Technical Report U.S.\ Department of Energy, BER and ASCR, 2017.
doi link bibtex

@TechReport{AXICCS16,
  author      = {Katherine Evans and Esmond G. Ng and Peter Caldwell and Forrest M. Hoffman and Charles Jackson and Kerstin {Kleese van Dam} and Lai-Yung Leung and Dan Martin and George Ostrouchov and Raymond Tuminaro and Paul Ullrich and Stefan M. Wild and Samuel Williams},
  institution = {U.S.\ Department of Energy, BER and ASCR},
  title       = {Advancing Cross-Cutting Ideas for Computational Climate Science},
  doi         = {10.2172/1341564},
  type        = {Workshop Report},
  year        = {2017},
}

Bragg Coherent Modulation Imaging: Strain- and Defect-Sensitive Single Views of Extended Samples. Ulvestad, A.; Cha, W.; Calvo-Almazan, I.; Maddali, S.; Wild, S. M.; Maxey, E.; Dupraz, M.; and Hruszkewycz, S. O. Technical Report Argonne National Laboratory, MCS Division, 2017.

Bragg Coherent Modulation Imaging: Strain- and Defect-Sensitive Single Views of Extended Samples [link]

Paper link bibtex

@TechReport{Ulvestad17,
  author      = {Andrew Ulvestad and Wonsuk Cha and Irene Calvo-Almazan and Siddharth Maddali and Stefan M. Wild and Evan Maxey and Maxime Dupraz and Stephan O. Hruszkewycz},
  institution = {Argonne National Laboratory, MCS Division},
  title       = {Bragg Coherent Modulation Imaging: Strain- and Defect-Sensitive Single Views of Extended Samples},
  url         = {https://arxiv.org/abs/1808.00115},
  anumber     = {ANL/MCS-PXXXX-0917},
  year        = {2017},
}

Solving Derivative-Free Nonlinear Least Squares Problems with POUNDERS. Wild, S. M. In Terlaky, T.; Anjos, M. F.; and Ahmed, S., editor(s), Advances and Trends in Optimization with Engineering Applications, pages 529–540. SIAM, 2017.
doi link bibtex

@InCollection{SWCHAP14,
  author    = {Stefan M. Wild},
  booktitle = {Advances and Trends in Optimization with Engineering Applications},
  title     = {Solving Derivative-Free Nonlinear Least Squares Problems with {POUNDERS}},
  doi       = {10.1137/1.9781611974683.ch40},
  editor    = {Tamas Terlaky and Miguel F. Anjos and Shabbir Ahmed},
  pages     = {529--540},
  publisher = {SIAM},
  aisbn     = {978-1-611974-67-6},
  anumber   = {ANL/MCS-P5120-0414},
  aurl      = {http://www.mcs.anl.gov/papers/P5120-0414.pdf},
  gurl      = {https://scholar.google.com/scholar?cluster=13543367487516072495},
  year      = {2017},
}

Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity. Madireddy, S.; Balaprakash, P.; Carns, P.; Latham, R.; Ross, R.; Snyder, S.; and Wild, S. M. In 2017 International Conference on Networking, Architecture, and Storage (NAS), pages 1–10, 2017. IEEE
doi link bibtex

@InProceedings{Madireddy17,
  author    = {Sandeep Madireddy and Prasanna Balaprakash and Philip Carns and Robert Latham and Robert Ross and Shane Snyder and Stefan M. Wild},
  booktitle = {2017 International Conference on Networking, Architecture, and Storage ({NAS})},
  title     = {Analysis and Correlation of Application {I/O} Performance and System-Wide {I/O} Activity},
  doi       = {10.1109/nas.2017.8026844},
  pages     = {1--10},
  publisher = {IEEE},
  anumber   = {ANL/MCS-P7036-0417},
  aurl      = {http://www.mcs.anl.gov/papers/P7036-0417.pdf},
  year      = {2017},
}

CONORBIT: Constrained Optimization by Radial Basis Function Interpolation in Trust Regions. Regis, R. G.; and Wild, S. M. Optimization Methods and Software, 32(3): 552–580. 2017.
doi link bibtex

@Article{CONORBIT15,
  author  = {Rommel G. Regis and Stefan M. Wild},
  title   = {{CONORBIT: Constrained} Optimization by Radial Basis Function Interpolation in Trust Regions},
  doi     = {10.1080/10556788.2016.1226305},
  number  = {3},
  pages   = {552--580},
  volume  = {32},
  anumber = {ANL/MCS-P5416-1015},
  aurl    = {http://www.mcs.anl.gov/papers/P5416-1015.pdf},
  gurl    = {https://scholar.google.com/scholar?cluster=15092247905949487231},
  journal = {Optimization Methods and Software},
  year    = {2017},
}

Joint Reconstruction of X-Ray Fluorescence and Transmission Tomography. Di, Z. W.; Chen, S.; Hong, Y. P.; Jacobsen, C.; Leyffer, S.; and Wild, S. M. Optics Express, 25(12): 13107–13124. 2017.
doi link bibtex

@Article{Di17,
  author  = {Zichao Wendy Di and Si Chen and Young Pyo Hong and Chris Jacobsen and Sven Leyffer and Stefan M. Wild},
  title   = {Joint Reconstruction of {X}-Ray Fluorescence and Transmission Tomography},
  doi     = {10.1364/oe.25.013107},
  number  = {12},
  pages   = {13107--13124},
  volume  = {25},
  anumber = {ANL/MCS-P6044-1016},
  journal = {Optics Express},
  year    = {2017},
}

Improving FPGA Design Parameter Exploration: Timing, Power, and Area. Mametjanov, A.; Balaprakash, P.; Choudary, C.; Hovland, P. D.; Wild, S. M.; Sabin, G.; and Wolfe, G. Technical Report ANL/MCS-P7000-0117, Argonne National Laboratory, MCS Division, 2017.

Improving FPGA Design Parameter Exploration: Timing, Power, and Area [pdf]

Paper link bibtex

@TechReport{ORFPGA17,
  author      = {Azamat Mametjanov and Prasanna Balaprakash and Chekuri Choudary and Paul D. Hovland and Stefan M. Wild and Gerald Sabin and Glenn Wolfe},
  institution = {Argonne National Laboratory, MCS Division},
  title       = {Improving {FPGA} Design Parameter Exploration: Timing, Power, and Area},
  number      = {ANL/MCS-P7000-0117},
  url         = {http://www.mcs.anl.gov/papers/P7000-0117.pdf},
  year        = {2017},
}

Uncertainty Quantification for Optical Model Parameters. Lovell, A. E.; Nunes, F. M.; Sarich, J.; and Wild, S. M. Physical Review C, 95(2): 024611. 2017.
doi link bibtex

@Article{Lovell17,
  author      = {Amy E. Lovell and Filomena M. Nunes and Jason Sarich and Stefan M. Wild},
  title       = {Uncertainty Quantification for Optical Model Parameters},
  doi         = {10.1103/PhysRevC.95.024611},
  number      = {2},
  pages       = {024611},
  volume      = {95},
  anumber     = {ANL/MCS-P6085-1116},
  arxivnumber = {arXiv:1611.01526},
  journal     = {Physical Review C},
  year        = {2017},
}

Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Foster, I.; Ainsworth, M.; Allen, B.; Bessac, J.; Cappello, F.; Choi, J. Y.; Constantinescu, E. M.; Davis, P. E.; Di, S.; Di, Z. W.; Guo, H.; Klasky, S.; Kleese van Dam, K.; Kurc, T.; Liu, Q.; Malik, A.; Mehta, K.; Mueller, K.; Munson, T.; Ostrouchov, G.; Parashar, M.; Peterka, T.; Pouchard, L.; Tao, D.; Tugluk, O.; Wild, S. M.; Wolf, M.; Wozniak, J. M.; Xu, W.; and Yoo, S. In Rivera, F. F.; Pena, T. F.; and Cabaleiro, J. C., editor(s), European Conference on Parallel Processing, pages 3–19, 2017. Springer
doi link bibtex

@InProceedings{CODAR2017,
  author    = {Foster, Ian and Ainsworth, Mark and Allen, Bryce and Bessac, Julie and Cappello, Franck and Choi, Jong Youl and Constantinescu, Emil M. and Davis, Philip E. and Di, Sheng and Di, Zichao Wendy and Guo, Hanqi and Klasky, Scott and {Kleese van Dam}, Kerstin and Kurc, Tahsin and Liu, Qing and Malik, Abid and Mehta, Kshitij and Mueller, Klaus and Munson, Todd and Ostrouchov, George and Parashar, Manish and Peterka, Tom and Pouchard, Line and Tao, Dingwen and Tugluk, Ozan and Wild, Stefan M. and Wolf, Matthew and Wozniak, Justin M. and Xu, Wei and Yoo, Shinjae},
  booktitle = {European Conference on Parallel Processing},
  title     = {Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales},
  doi       = {10.1007/978-3-319-64203-1_1},
  editor    = {Rivera, Francisco F. and Pena, Tom{\'a}s F. and Cabaleiro, Jos{\'e} C.},
  pages     = {3--19},
  publisher = {Springer},
  anote     = {Euro-Par 2017: Parallel Processing: 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28 -- September 1, 2017, Proceedings},
  year      = {2017},
}

2016 (17)

Report of the DOE Workshop on Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing. Bethel, E. W.; and Greenwald (eds.), M. Technical Report U.S.\ Department of Energy, ASCR, 2016.
doi link bibtex

@TechReport{ASCR-EOD-Workshop-Report:2015,
  author      = {E. Wes Bethel and Martin {Greenwald (eds.)}},
  institution = {{U.S.\ Department of Energy, ASCR}},
  title       = {Report of the {DOE} Workshop on Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing},
  doi         = {10.2172/1525145},
  type        = {Report},
  anote       = {LBNL-1005155},
  year        = {2016},
}

AutoMOMML: Automatic Multi-Objective Modeling with Machine Learning. Balaprakash, P.; Tiwari, A.; Wild, S. M.; Carrington, L.; and Hovland, P. D. In Kunkel, M. J.; Balaji, P.; and Dongarra, J., editor(s), High Performance Computing: 31st International Conference, ISC High Performance 2016, Frankfurt, Germany, June 19-23, 2016, Proceedings, pages 219–239, 2016. Springer
doi link bibtex

@InProceedings{Automomml15,
  author    = {Prasanna Balaprakash and Ananta Tiwari and Stefan M. Wild and Laura Carrington and Paul D. Hovland},
  booktitle = {High Performance Computing: 31st International Conference, ISC High Performance 2016, Frankfurt, Germany, June 19-23, 2016, Proceedings},
  title     = {{AutoMOMML: Automatic} Multi-Objective Modeling with Machine Learning},
  doi       = {10.1007/978-3-319-41321-1_12},
  editor    = {Kunkel, M. Julian and Balaji, Pavan and Dongarra, Jack},
  pages     = {219--239},
  publisher = {Springer},
  anumber   = {ANL/MCS-P5421-1015},
  pnote     = {International Supercomputing Conference -- High Performance (ISC-HPC 2016)},
  year      = {2016},
}

Doing Moore with Less – Leapfrogging Moore's Law with Inexactness for Supercomputing. Leyffer, S.; Wild, S. M.; Fagan, M.; Snir, M.; Palem, K.; Finkel, H.; and Yoshii, K. Technical Report ANL/MCS-P6077-1016, Argonne National Laboratory MCS, 2016.

Paper link bibtex

@TechReport{Palem16,
  author      = {Sven Leyffer and Stefan M. Wild and Mike Fagan and Marc Snir and Krishna Palem and Hal Finkel and Kazutomo Yoshii},
  institution = {Argonne National Laboratory MCS},
  title       = {Doing {Moore} with Less -- Leapfrogging {Moore's} Law with Inexactness for Supercomputing},
  number      = {ANL/MCS-P6077-1016},
  type        = {Technical Report},
  url         = {https://arxiv.org/abs/1610.02606},
  year        = {2016},
}

Exploiting Performance Portability in Search Algorithms for Autotuning. Roy, A.; Balaprakash, P.; Hovland, P. D.; and Wild, S. M. In 2016 IEEE International Parallel and Distributed Processing Symposium IPDPS Workshops, pages 1535–1544, 2016.
doi link bibtex

@InProceedings{Roy15,
  author    = {Amit Roy and Prasanna Balaprakash and Paul D. Hovland and Stefan M. Wild},
  booktitle = {2016 {IEEE} International Parallel and Distributed Processing Symposium {IPDPS} Workshops},
  title     = {Exploiting Performance Portability in Search Algorithms for Autotuning},
  doi       = {10.1109/IPDPSW.2016.85},
  pages     = {1535--1544},
  anote     = {Eleventh International Workshop on Automatic Performance Tuning (iWAPT2016)},
  anumber   = {ANL/MCS-P5397-0915},
  aurl      = {http://www.mcs.anl.gov/papers/P5397-0915.pdf},
  year      = {2016},
}

Rejoinder: Modeling an Augmented Lagrangian for Blackbox Constrained Optimization. Gramacy, R. B.; Gray, G. A.; Le Digabel, S.; Lee, H. K. H.; Ranjan, P.; Wells, G.; and Wild, S. M. Technometrics, 58(1): 26–29. 2016.
doi link bibtex

@Article{AugLag14r,
  author  = {Robert B. Gramacy and Genetha A. Gray and S\'ebastien {Le Digabel} and Herbert K. H. Lee and Pritam Ranjan and Garth Wells and Stefan M. Wild},
  title   = {Rejoinder: Modeling an Augmented {Lagrangian} for Blackbox Constrained Optimization},
  doi     = {10.1080/00401706.2015.1106979},
  number  = {1},
  pages   = {26--29},
  volume  = {58},
  anumber = {ANL/MCS-P5401-0915},
  journal = {Technometrics},
  year    = {2016},
}

Novel Large Scale Simulation Process to Support DOT's CAFE Modeling System. Moawad, A.; Balaprakash, P.; Rousseau, A.; and Wild, S. M. International Journal of Automotive Technology, 17(6): 1067–1077. 2016.
doi link bibtex

@Article{DOT15j,
  author  = {Ayman Moawad and Prasanna Balaprakash and Aymeric Rousseau and Stefan M. Wild},
  title   = {Novel Large Scale Simulation Process to Support {DOT}'s {CAFE} Modeling System},
  doi     = {10.1007/s12239-016-0104-z},
  number  = {6},
  pages   = {1067--1077},
  volume  = {17},
  anote   = {P5292-0215},
  journal = {International Journal of Automotive Technology},
  year    = {2016},
}

Origins and Optimization of Entanglement in Plasmonically Coupled Quantum Dots. Otten, M.; Larson, J.; Min, M.; Wild, S. M.; Pelton, M.; and Gray, S. K. Physical Review A, 94(2): 022312. 2016.
doi link bibtex

@Article{Otten16,
  author  = {Matthew Otten and Jeffrey Larson and Misun Min and Stefan M. Wild and Matthew Pelton and Stephen K. Gray},
  title   = {Origins and Optimization of Entanglement in Plasmonically Coupled Quantum Dots},
  doi     = {10.1103/PhysRevA.94.022312},
  number  = {2},
  pages   = {022312},
  volume  = {94},
  anumber = {ANL/MCS-P5567-0416},
  aurl    = {http://www.mcs.anl.gov/papers/P5567-0416.pdf},
  journal = {Physical Review A},
  year    = {2016},
}

Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing. Bethel, E. W.; Greenwald, M.; Kleese van Dam, K.; Parashar, M.; Wild, S. M.; and Wiley, H. S. In 2016 IEEE 12th International Conference on e-Science, pages 213–222, 2016.
doi link bibtex

@InProceedings{Esci16,
  author    = {E. Wes Bethel and Martin Greenwald and Kerstin {Kleese van Dam} and Manish Parashar and Stefan M. Wild and H. Steven Wiley},
  booktitle = {2016 IEEE 12th International Conference on e-Science},
  title     = {Management, Analysis, and Visualization of Experimental and Observational Data -- The Convergence of Data and Computing},
  doi       = {10.1109/eScience.2016.7870902},
  pages     = {213--222},
  anumber   = {ANL/MCS-P6017-0616},
  year      = {2016},
}

Bayesian Optimization under Mixed Constraints with a Slack-Variable Augmented Lagrangian. Picheny, V.; Gramacy, R. B.; Wild, S. M.; and Le Digabel, S. In Lee, D. D.; Sugiyama, M.; Luxburg, U. V.; Guyon, I.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 29, pages 1435–1443, 2016. Curran Associates, Inc.

Bayesian Optimization under Mixed Constraints with a Slack-Variable Augmented Lagrangian [pdf]

Paper link bibtex

@InProceedings{ALSlack16,
  author    = {Victor Picheny and Robert B. Gramacy and Stefan M. Wild and S\'ebastien {Le Digabel}},
  booktitle = {Advances in Neural Information Processing Systems 29},
  title     = {Bayesian Optimization under Mixed Constraints with a Slack-Variable Augmented {Lagrangian}},
  editor    = {D. D. Lee and M. Sugiyama and U. V. Luxburg and I. Guyon and R. Garnett},
  pages     = {1435--1443},
  publisher = {Curran Associates, Inc.},
  url       = {https://papers.neurips.cc/paper/6439-bayesian-optimization-under-mixed-constraints-with-a-slack-variable-augmented-lagrangian.pdf},
  anumber   = {ANL/MCS-P6012-0516},
  aurl      = {1605.09466},
  gurl      = {https://scholar.google.com/scholar?cluster=16495590784822835370},
  year      = {2016},
}

Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion. Di, Z. W.; Leyffer, S.; and Wild, S. M. SIAM Journal on Imaging Sciences, 9(1): 1–23. 2016.
doi link bibtex

@Article{Di15,
  author  = {Zichao Wendy Di and Sven Leyffer and Stefan M. Wild},
  title   = {Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion},
  doi     = {10.1137/15M1021404},
  number  = {1},
  pages   = {1--23},
  volume  = {9},
  anumber = {ANL/MCS-P5327-0415},
  aurl    = {http://www.mcs.anl.gov/papers/P5327-0415.pdf},
  journal = {SIAM Journal on Imaging Sciences},
  year    = {2016},
}

Overcoming the Power Wall by Exploiting Application Inexactness and Emerging COTS Architectural Features: Trading Precision for Improving Application Quality. Fagan, M.; Schlachter, J.; Yoshii, K.; Leyffer, S.; Palem, K.; Snir, M.; Wild, S. M.; and Enz, C. In 29th IEEE International System-on-Chip Conference (SOCC), pages 241–246, 2016.
doi link bibtex

@InProceedings{Fagan16,
  author    = {Mike Fagan and Jeremy Schlachter and Kazutomo Yoshii and Sven Leyffer and Krishna Palem and Marc Snir and Stefan M. Wild and Christian Enz},
  booktitle = {29th IEEE International System-on-Chip Conference (SOCC)},
  title     = {Overcoming the Power Wall by Exploiting Application Inexactness and Emerging {COTS} Architectural Features: {Trading} Precision for Improving Application Quality},
  doi       = {10.1109/SOCC.2016.7905477},
  pages     = {241--246},
  anumber   = {ANL/MCS-P6040-0816},
  year      = {2016},
}

Single-View Phase Retrieval of an Extended Sample by Exploiting Edge Detection and Sparsity. Tripathi, A.; McNulty, I.; Munson, T.; and Wild, S. M. Optics Express, 24(21): 24719–24738. 2016.
doi link bibtex

@Article{TripathiSV16,
  author  = {Ashish Tripathi and Ian McNulty and Todd Munson and Stefan M. Wild},
  title   = {Single-View Phase Retrieval of an Extended Sample by Exploiting Edge Detection and Sparsity},
  doi     = {10.1364/OE.24.024719},
  number  = {21},
  pages   = {24719--24738},
  volume  = {24},
  anumber = {ANL/MCS-P6028-0716},
  journal = {Optics Express},
  year    = {2016},
}

Coherent Diffractive Imaging of Time-Evolving Samples with Improved Temporal Resolution. Ulvestad, A.; Tripathi, A.; Hruszkewycz, S. O.; Cha, W.; Fuoss, P. H.; Wild, S. M.; and Stephenson, G. B. Physical Review B, 93(18): 184105. 2016.
doi link bibtex

@Article{ChronoCDI16,
  author  = {Andrew Ulvestad and Ash Tripathi and Stephan O. Hruszkewycz and Wonsuk Cha and Paul H. Fuoss and Stefan M. Wild and G. Brian Stephenson},
  title   = {Coherent Diffractive Imaging of Time-Evolving Samples with Improved Temporal Resolution},
  doi     = {10.1103/PhysRevB.93.184105},
  number  = {18},
  pages   = {184105},
  volume  = {93},
  anumber = {ANL/MCS-P5430-1115},
  journal = {Physical Review B},
  year    = {2016},
}

Manifold Sampling for $\ell_1$ Nonconvex Optimization. Larson, J.; Menickelly, M.; and Wild, S. M. SIAM Journal on Optimization, 26(4): 2540–2563. 2016.
doi link bibtex

@Article{LMW16,
  author  = {Jeffrey Larson and Matt Menickelly and Stefan M. Wild},
  title   = {Manifold Sampling for $\ell_1$ Nonconvex Optimization},
  doi     = {10.1137/15M1042097},
  number  = {4},
  pages   = {2540--2563},
  volume  = {26},
  anumber = {ANL/MCS-P5392-0915},
  aurl    = {http://www.mcs.anl.gov/papers/P5392-0915.pdf},
  gurl    = {https://scholar.google.com/scholar?cluster=17516614248802038308},
  journal = {SIAM Journal on Optimization},
  year    = {2016},
}

A Batch, Derivative-Free Algorithm for Finding Multiple Local Minima. Larson, J.; and Wild, S. M. Optimization and Engineering, 17(1): 205–228. 2016.
doi link bibtex

@Article{LarWild14,
  author  = {Jeffrey Larson and Stefan M. Wild},
  title   = {A Batch, Derivative-Free Algorithm for Finding Multiple Local Minima},
  doi     = {10.1007/s11081-015-9289-7},
  number  = {1},
  pages   = {205--228},
  volume  = {17},
  gurl    = {https://scholar.google.com/scholar?cluster=15336371664648065295},
  journal = {Optimization and Engineering},
  mnote   = {ANL/MCS-P5228-1114},
  year    = {2016},
}

Modeling an Augmented Lagrangian for Blackbox Constrained Optimization. Gramacy, R. B.; Gray, G. A.; Le Digabel, S.; Lee, H. K. H.; Ranjan, P.; Wells, G.; and Wild, S. M. Technometrics, 58(1): 1–11. 2016.
doi link bibtex

@Article{AugLag14,
  author    = {Robert B. Gramacy and Genetha A. Gray and S\'ebastien {Le Digabel} and Herbert K. H. Lee and Pritam Ranjan and Garth Wells and Stefan M. Wild},
  title     = {Modeling an Augmented {Lagrangian} for Blackbox Constrained Optimization},
  doi       = {10.1080/00401706.2015.1014065},
  number    = {1},
  pages     = {1--11},
  volume    = {58},
  journal   = {Technometrics},
  mcsnumber = {ANL/MCS-P5109-0314},
  year      = {2016},
}

Non-Negative Matrix Analysis in X-Ray Spectromicroscopy: Choosing Regularizers. Mak, R.; Wild, S. M.; and Jacobsen, C. AIP Conference Proceedings, 1696: 020034. 2016. 12th International Conference on X-Ray Microscopy (XRM 2014)
doi link bibtex

@Article{Mak15,
  author  = {Rachel Mak and Stefan M. Wild and Chris Jacobsen},
  title   = {Non-Negative Matrix Analysis in X-Ray Spectromicroscopy: Choosing Regularizers},
  doi     = {10.1063/1.4937528},
  note    = {12th International Conference on X-Ray Microscopy (XRM 2014)},
  pages   = {020034},
  volume  = {1696},
  anumber = {ANL/MCS-5328-0415},
  journal = {AIP Conference Proceedings},
  year    = {2016},
}

2015 (18)

A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model. Higdon, D.; McDonnell, J. D.; Schunck, N.; Sarich, J.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 42(3): 034009. 2015.
doi link bibtex

@Article{HigdonJPG15,
  author  = {Dave Higdon and Jordan D. McDonnell and Nicolas Schunck and Jason Sarich and Stefan M. Wild},
  title   = {A {Bayesian} Approach for Parameter Estimation and Prediction using a Computationally Intensive Model},
  doi     = {10.1088/0954-3899/42/3/034009},
  number  = {3},
  pages   = {034009},
  volume  = {42},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  mnote   = {P5159-0714},
  year    = {2015},
}

Quantification of Uncertainties in Nuclear Density Functional Theory. Schunck, N.; McDonnell, J. D.; Sarich, J.; Wild, S. M.; and Higdon, D. Nuclear Data Sheets, 123: 115–118. 2015.
doi link bibtex

@Article{NDS15,
  author  = {Nicolas Schunck and Jordan D. McDonnell and Jason Sarich and Stefan M. Wild and Dave Higdon},
  title   = {Quantification of Uncertainties in Nuclear Density Functional Theory},
  doi     = {10.1016/j.nds.2014.12.020},
  pages   = {115--118},
  volume  = {123},
  anote   = {ANL/MCS-P5144-0514},
  journal = {Nuclear Data Sheets},
  year    = {2015},
}

Uncertainty Quantification and Propagation in Nuclear Density Functional Theory. Schunck, N.; McDonnell, J. D.; Higdon, D.; Sarich, J.; and Wild, S. M. European Physical Journal A, 51(12): 169(1–14). 2015.
doi link bibtex

@Article{SchunckEPJ15,
  author  = {Nicolas Schunck and Jordan D. McDonnell and Dave Higdon and Jason Sarich and Stefan M. Wild},
  title   = {Uncertainty Quantification and Propagation in Nuclear Density Functional Theory},
  doi     = {10.1140/epja/i2015-15169-9},
  number  = {12},
  pages   = {169(1--14)},
  volume  = {51},
  anumber = {1503.05894},
  journal = {European Physical Journal A},
  mnumber = {ANL/MCS-P5339-0415},
  year    = {2015},
}

Error Analysis in Nuclear Density Functional Theory. Schunck, N.; McDonnell, J. D.; Sarich, J.; Wild, S. M.; and Higdon, D. Journal of Physics G: Nuclear and Particle Physics, 42(3): 034024. 2015.
doi link bibtex

@Article{SchunckJPG15,
  author  = {Nicolas Schunck and Jordan D. McDonnell and Jason Sarich and Stefan M. Wild and Dave Higdon},
  title   = {Error Analysis in Nuclear Density Functional Theory},
  doi     = {10.1088/0954-3899/42/3/034024},
  number  = {3},
  pages   = {034024},
  volume  = {42},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  mnote   = {P5145-0514},
  year    = {2015},
}

One-Nucleon Transfer Reactions and the Optical Potential. Nunes, F. M.; Lovell, A. E.; Ross, A.; Titus, L. J.; Charity, R. J.; Dickhoff, W. H.; Mahzoon, M. H.; Sarich, J.; and Wild, S. M. In Proceedings, 14th International Conference on Nuclear Reaction Mechanisms: Varenna, Italy, June 15-19, 2015, pages 123–130, 2015.

One-Nucleon Transfer Reactions and the Optical Potential [pdf]

Paper link bibtex

@InProceedings{Nunes15,
  author    = {Nunes, Filomena M. and Lovell, Amy E. and Ross, Alaina and Titus, Luke J. and Charity, R. J. and Willem Hendrik Dickhoff and M. Hossein Mahzoon and Jason Sarich and Stefan M. Wild},
  booktitle = {Proceedings, 14th International Conference on Nuclear Reaction Mechanisms: Varenna, Italy, June 15-19, 2015},
  title     = {One-Nucleon Transfer Reactions and the Optical Potential},
  pages     = {123--130},
  url       = {http://inspirehep.net/record/1393533/files/arXiv:1509.04700.pdf},
  anumber   = {ANL/MCS-P5403-0915},
  aurl      = {http://arxiv.org/abs/1509.04700},
  year      = {2015},
}

Statistical Uncertainties of a Chiral Interaction at Next-to-Next-To Leading Order. Ekström, A.; Carlsson, B. D.; Wendt, K.; Forssén, C.; Hjorth-Jensen, M.; Machleidt, R.; and Wild, S. M. Journal of Physics G: Nuclear and Particle Physics, 42(3): 034003. 2015.
doi link bibtex

@Article{EksJPG15,
  author  = {Andreas Ekstr\"om and Boris D. Carlsson and Kyle Wendt and Christian Forss\'en and Morten Hjorth-Jensen and Ruprecht Machleidt and Stefan M. Wild},
  title   = {Statistical Uncertainties of a Chiral Interaction at Next-to-Next-To Leading Order},
  doi     = {10.1088/0954-3899/42/3/034003},
  number  = {3},
  pages   = {034003},
  volume  = {42},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  mnote   = {P5156-0614},
  year    = {2015},
}

Nuclear Energy Density Optimization: UNEDF2. Kortelainen, M.; McDonnell, J. D.; Nazarewicz, W.; Olsen, E.; Reinhard, P.; Sarich, J.; Schunck, N.; Wild, S. M.; Davesne, D.; Erler, J.; and Pastore, A. In JPS Conference Proceedings, volume 6, pages 020018, 2015.
doi link bibtex

@InProceedings{MKUNEDF2,
  author    = {M. Kortelainen and J. D. McDonnell and W. Nazarewicz and E. Olsen and P.-G. Reinhard and J. Sarich and N. Schunck and S. M. Wild and D. Davesne and J. Erler and A. Pastore},
  booktitle = {JPS Conference Proceedings},
  title     = {Nuclear Energy Density Optimization: {UNEDF2}},
  doi       = {10.7566/JPSCP.6.020018},
  pages     = {020018},
  volume    = {6},
  anote     = {Proceedings of the Conference on Advances in Radioactive Isotope Science (ARIS2014)},
  year      = {2015},
}

Collective I/O Tuning Using Analytical and Machine Learning Models. Isaila, F.; Balaprakash, P.; Wild, S. M.; Kimpe, D.; Latham, R.; Ross, R.; and Hovland, P. D. In Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2015), pages 128–137, 2015.
doi link bibtex

@InProceedings{HybridIO15,
  author    = {Florin Isaila and Prasanna Balaprakash and Stefan M. Wild and Dries Kimpe and Rob Latham and Rob Ross and Paul D. Hovland},
  booktitle = {Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2015)},
  title     = {Collective {I/O} Tuning Using Analytical and Machine Learning Models},
  doi       = {10.1109/CLUSTER.2015.29},
  pages     = {128--137},
  aurl      = {http://www.mcs.anl.gov/papers/P5264-1214.pdf},
  mnumber   = {ANL/MCS-P5264-1214},
  year      = {2015},
}

Using Multiobjective Optimization for Automotive Component Sizing. Vijayagopal, R.; Chen, R.; Sharer, P.; Wild, S. M.; and Rousseau, A. World Electric Vehicle Journal, 7(2): 261–269. 2015.
doi link bibtex

@Article{Vijayagopal15,
  author     = {R. Vijayagopal and R. Chen and P. Sharer and S. M. Wild and A. Rousseau},
  title      = {Using Multiobjective Optimization for Automotive Component Sizing},
  doi        = {10.3390/wevj7020261},
  number     = {2},
  pages      = {261--269},
  volume     = {7},
  abooktitle = {Proceedings of the International Electric Vehicle Symposium and Exhibition},
  anote      = {Paper number EVS28\_0153:D3-03},
  journal    = {World Electric Vehicle Journal},
  year       = {2015},
}

Dynamic Model-Driven Parallel I/O Performance Tuning. Behzad, B.; Byna, S.; Wild, S. M.; Prabhat; and Snir, M. In Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2015), pages 184–193, 2015.
doi link bibtex

@InProceedings{Behzad15,
  author    = {Babak Behzad and Surendra Byna and Stefan M. Wild and {Prabhat} and Marc Snir},
  booktitle = {Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2015)},
  title     = {Dynamic Model-Driven Parallel {I/O} Performance Tuning},
  doi       = {10.1109/CLUSTER.2015.37},
  pages     = {184--193},
  aurl      = {http://www.mcs.anl.gov/papers/P5278-0115.pdf},
  mnumber   = {ANL/MCS-P5278-0115},
  year      = {2015},
}

Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements. McDonnell, J. D.; Schunck, N.; Higdon, D.; Sarich, J.; Wild, S. M.; and Nazarewicz, W. Physical Review Letters, 114(12): 122501. 2015.
doi link bibtex

@Article{McDonnellPRL15,
  author    = {Jordan D. McDonnell and Nicolas Schunck and Dave Higdon and Jason Sarich and Stefan M. Wild and Witold Nazarewicz},
  title     = {Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements},
  doi       = {10.1103/PhysRevLett.114.122501},
  number    = {12},
  pages     = {122501},
  volume    = {114},
  adsnumber = {ANL/MCS-P5270-0115},
  journal   = {Physical Review Letters},
  year      = {2015},
}

ACCOLADES: A Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines. Aithal, S. M.; and Wild, S. M. In Kunkel, J. M.; and Ludwig, T., editor(s), High Performance Computing (ISC-HPC 2015), volume 9137, pages 87–95, 2015. Springer
doi link bibtex

@InProceedings{SASW15isc,
  author    = {Shashi M. Aithal and Stefan M. Wild},
  booktitle = {High Performance Computing (ISC-HPC 2015)},
  title     = {{ACCOLADES: A} Scalable Workflow Framework for Large-Scale Simulation and Analyses of Automotive Engines},
  doi       = {10.1007/978-3-319-20119-1_7},
  editor    = {Kunkel, Julian M. and Ludwig, Thomas},
  pages     = {87--95},
  publisher = {Springer},
  volume    = {9137},
  anote     = {International Supercomputing Conference -- High Performance (ISC-HPC 2015)},
  aseries   = {Lecture Notes in Computer Science},
  mnote     = {ANL/MCS-5294-0215},
  year      = {2015},
}

Analysis of the Tradeoffs between Energy and Run Time for Multilevel Checkpointing. Balaprakash, P.; Bautista Gomez, L. A.; Bouguerra, M.; Wild, S. M.; Cappello, F.; and Hovland, P. D. In Jarvis, S. A.; Wright, S. A.; and Hammond, S. D., editor(s), High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, volume 8966, pages 249–263, 2015. Springer
doi link bibtex

@InProceedings{ResTrade14,
  author    = {Prasanna Balaprakash and Leonardo A. {Bautista Gomez} and Mohamed-Slim Bouguerra and Stefan M. Wild and Franck Cappello and Paul D. Hovland},
  booktitle = {High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation},
  title     = {Analysis of the Tradeoffs between Energy and Run Time for Multilevel Checkpointing},
  doi       = {10.1007/978-3-319-17248-4_13},
  editor    = {Jarvis, Stephen A. and Wright, Steven A. and Hammond, Simon D.},
  pages     = {249--263},
  publisher = {Springer},
  volume    = {8966},
  anote     = {P5138-0514},
  aseries   = {Lecture Notes in Computer Science},
  snote     = {Proceedings of the 5th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS14)},
  year      = {2015},
}

Derivative-Free Optimization for Parameter Estimation in Computational Nuclear Physics. Wild, S. M.; Sarich, J.; and Schunck, N. Journal of Physics G: Nuclear and Particle Physics, 42(3): 034031. 2015.
doi link bibtex

@Article{WSS15,
  author  = {Stefan M. Wild and Jason Sarich and Nicolas Schunck},
  title   = {Derivative-Free Optimization for Parameter Estimation in Computational Nuclear Physics},
  doi     = {10.1088/0954-3899/42/3/034031},
  number  = {3},
  pages   = {034031},
  volume  = {42},
  journal = {Journal of Physics G: Nuclear and Particle Physics},
  mnote   = {P5149-0614},
  year    = {2015},
}

A Taxonomy of Constraints in Black-Box Simulation-Based Optimization. Le Digabel, S.; and Wild, S. M. Technical Report ANL/MCS-P5350-0515, Argonne National Laboratory, MCS, 2015.

A Taxonomy of Constraints in Black-Box Simulation-Based Optimization [pdf]

Paper link bibtex

@TechReport{taxonomy15,
  author      = {S\'ebastien {Le Digabel} and Stefan M. Wild},
  institution = {Argonne National Laboratory, MCS},
  title       = {A Taxonomy of Constraints in Black-Box Simulation-Based Optimization},
  number      = {ANL/MCS-P5350-0515},
  url         = {http://www.mcs.anl.gov/papers/P5350-0515.pdf},
  anumber     = {arXiv:1505.07881},
  gurl        = {https://scholar.google.com/scholar?cluster=8245889514910760898},
  year        = {2015},
}

Development of a Reduced-Order Design/Optimization Tool for Automotive Engines Using Massively Parallel Computing. Aithal, S. M.; and Wild, S. M. In Proceedings of the SAE 12th International Conference on Engines & Vehicles, 2015.
doi link bibtex

@InProceedings{SASW15ice,
  author     = {Shashi M. Aithal and Stefan M. Wild},
  booktitle  = {Proceedings of the SAE 12th International Conference on Engines \& Vehicles},
  title      = {Development of a Reduced-Order Design/Optimization Tool for Automotive Engines Using Massively Parallel Computing},
  doi        = {10.4271/2015-24-2390},
  anote      = {SAE Technical Paper 2015-24-2390},
  apublisher = {SAE},
  mnote      = {5354-0615},
  year       = {2015},
}

Visualizing and Improving the Robustness of Phase Retrieval Algorithms. Tripathi, A.; Leyffer, S.; Munson, T.; and Wild, S. M. Procedia Computer Science (ICCS 2015), 51: 815–824. 2015.
doi link bibtex

@Article{Tripathi15,
  author  = {Ashish Tripathi and Sven Leyffer and Todd Munson and Stefan M. Wild},
  title   = {Visualizing and Improving the Robustness of Phase Retrieval Algorithms},
  doi     = {10.1016/j.procs.2015.05.205},
  pages   = {815--824},
  volume  = {51},
  anote   = {International Conference on Computational Science, (ICCS) 2015},
  journal = {Procedia Computer Science (ICCS 2015)},
  mnote   = {ANL/MCS-5272-0115},
  year    = {2015},
}

Autotuning FPGA Design Parameters for Performance and Power. Mametjanov, A.; Balaprakash, P.; Choudary, C.; Hovland, P. D.; Wild, S. M.; and Sabin, G. In Proceedings of the 23rd IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2015), pages 84–91, 2015.
doi link bibtex

@InProceedings{ORFPGA15,
  author    = {Azamat Mametjanov and Prasanna Balaprakash and Chekuri Choudary and Paul D. Hovland and Stefan M. Wild and Gerald Sabin},
  booktitle = {Proceedings of the 23rd IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2015)},
  title     = {Autotuning {FPGA} Design Parameters for Performance and Power},
  doi       = {10.1109/FCCM.2015.54},
  pages     = {84--91},
  anumber   = {ANL/MCS-P5266-1214},
  year      = {2015},
}

2014 (11)

DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges. Lucas, R.; Ang, J.; Bergman, K.; Borkar, S.; Carlson, W.; Carrington, L.; Chiu, G.; Colwell, R.; Dally, W.; Dongarra, J.; Geist, A.; Haring, R.; Hittinger, J.; Hoisie, A.; Klein, D. M.; Kogge, P.; Lethin, R.; Sarkar, V.; Schreiber, R.; Shalf, J.; Sterling, T.; Stevens, R.; Bashor, J.; Brightwell, R.; Coteus, P.; Debenedictus, E.; Hiller, J.; Kim, K. H.; Langston, H.; Murphy, R. M.; Webster, C.; Wild, S.; Grider, G.; Ross, R.; Leyffer, S.; and Laros III, J. Technical Report U.S.\ Department of Energy, ASCR, 2014.
doi link bibtex

@TechReport{Exascale2014,
  author      = {Lucas, Robert and Ang, James and Bergman, Keren and Borkar, Shekhar and Carlson, William and Carrington, Laura and Chiu, George and Colwell, Robert and Dally, William and Dongarra, Jack and Geist, Al and Haring, Rud and Hittinger, Jeffrey and Hoisie, Adolfy and Klein, Dean Micron and Kogge, Peter and Lethin, Richard and Sarkar, Vivek and Schreiber, Robert and Shalf, John and Sterling, Thomas and Stevens, Rick and Bashor, Jon and Brightwell, Ron and Coteus, Paul and Debenedictus, Erik and Hiller, Jon and Kim, K. H. and Langston, Harper and Murphy, Richard Micron and Webster, Clayton and Wild, Stefan and Grider, Gary and Ross, Rob and Leyffer, Sven and Laros III, James},
  institution = {U.S.\ Department of Energy, ASCR},
  title       = {DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges},
  doi         = {10.2172/1222713},
  type        = {Report},
  year        = {2014},
}

Energy-Performance Tradeoffs in Multilevel Checkpoint Strategies (Poster). Bautista Gomez, L. A.; Balaprakash, P.; Bouguerra, M.; Wild, S. M.; Cappello, F.; and Hovland, P. D. In Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2014), pages 278–279, 2014.
doi link bibtex

@InProceedings{ResTrade14poster,
  author    = {Bautista Gomez, L. A. and Balaprakash, P. and Bouguerra, M.-S. and Wild, S. M. and Cappello, F. and Hovland, P. D.},
  booktitle = {Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2014)},
  title     = {Energy-Performance Tradeoffs in Multilevel Checkpoint Strategies (Poster)},
  doi       = {10.1109/CLUSTER.2014.6968749},
  pages     = {278--279},
  year      = {2014},
}

Empirical Performance Modeling of GPU Kernels Using Active Learning. Balaprakash, P.; Rupp, K.; Mametjanov, A.; Gramacy, R. B.; Hovland, P. D.; and Wild, S. M. In Bader, M.; Bode, A.; Bungartz, H.; Gerndt, M.; Joubert, G. R.; and Peters, F., editor(s), Parallel Computing: Accelerating Computational Science and Engineering (ParCo2013), volume 25, pages 646–655, 2014. IOS Press
doi link bibtex

@InProceedings{Parco13,
  author    = {Prasanna Balaprakash and Karl Rupp and Azamat Mametjanov and Robert B. Gramacy and Paul D. Hovland and Stefan M. Wild},
  booktitle = {Parallel Computing: Accelerating Computational Science and Engineering (ParCo2013)},
  title     = {Empirical Performance Modeling of {GPU} Kernels Using Active Learning},
  doi       = {10.3233/978-1-61499-381-0-646},
  editor    = {M. Bader and A. Bode and H.-J. Bungartz and M. Gerndt and G. R. Joubert and F. Peters},
  pages     = {646--655},
  publisher = {IOS Press},
  volume    = {25},
  anote     = {International Conference on Parallel Computing (ParCo2013)},
  aseries   = {Advances in Parallel Computing},
  year      = {2014},
}

SciDAC: Accelerating Scientific Discovery, Transforming Computational Science. D'Azevedo, E.; Ng, E. G.; and Wild, S. M. SIAM News, 47(3). 2014.

SciDAC: Accelerating Scientific Discovery, Transforming Computational Science [link]

Paper link bibtex

@Article{SciDAC14SN,
  author  = {Eduardo {D'Azevedo} and Esmond G. Ng and Stefan M. Wild},
  title   = {{SciDAC: Accelerating} Scientific Discovery, Transforming Computational Science},
  number  = {3},
  url     = {https://sinews.siam.org/About-the-Author/scidac-accelerating-scientific-discovery-transforming-computational-science},
  volume  = {47},
  journal = {SIAM News},
  year    = {2014},
}

Unsupervised Cell Identification on Multidimensional X-ray Fluorescence Datasets. Wang, S.; Ward, J.; Leyffer, S.; Vogt, S.; Wild, S. M.; and Jacobsen, C. Journal of Synchrotron Radiation, 21(3): 568–579. 2014.
doi link bibtex

@Article{Wang13,
  author  = {Siwei Wang and Jesse Ward and Sven Leyffer and Stefan Vogt and Stefan M. Wild and Chris Jacobsen},
  title   = {Unsupervised Cell Identification on Multidimensional {X-ray} Fluorescence Datasets},
  doi     = {10.1107/S1600577514001416},
  number  = {3},
  pages   = {568--579},
  volume  = {21},
  journal = {Journal of Synchrotron Radiation},
  year    = {2014},
}

Improving Parallel I/O Autotuning with Performance Modeling. Behzad, B.; Byna, S.; Wild, S. M.; Prabhat; and Snir, M. In Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing (HPDC14), pages 253–256, 2014. ACM
doi link bibtex

@InProceedings{IOAUTO14,
  author    = {Babak Behzad and Surendra Byna and Stefan M. Wild and {Prabhat} and Marc Snir},
  booktitle = {Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing (HPDC14)},
  title     = {Improving Parallel {I/O} Autotuning with Performance Modeling},
  doi       = {10.1145/2600212.2600708},
  pages     = {253--256},
  publisher = {ACM},
  alongver  = {http://www.mcs.anl.gov/papers/P5066-0114.pdf},
  anumber   = {ANL/MCS-P5066-0114},
  year      = {2014},
}

Applied Mathematics Research for Exascale Computing. Dongarra, J.; Hittinger, J.; Bell, J.; Chacón, L.; Falgout, R.; Heroux, M.; Hovland, P. D.; Ng, E. G.; Webster, C.; and Wild, S. M. Technical Report U.S.\ Department of Energy, ASCR, 2014.
doi link bibtex

@TechReport{EMWG14,
  author      = {Jack Dongarra and Jeffrey Hittinger and John Bell and Luis Chac\'on and Robert Falgout and Michael Heroux and Paul D. Hovland and Esmond G. Ng and Clayton Webster and Stefan M. Wild},
  institution = {U.S.\ Department of Energy, ASCR},
  title       = {Applied Mathematics Research for Exascale Computing},
  doi         = {10.2172/1149042},
  type        = {Report},
  year        = {2014},
}

Non-Negative Matrix Analysis for Effective Feature Extraction in X-ray Spectromicroscopy. Mak, R.; Lerotic, M.; Fleckenstein, H.; Vogt, S.; Wild, S. M.; Leyffer, S.; Sheynkin, Y.; and Jacobsen, C. Faraday Discussions, 171: 357–371. 2014.
doi link bibtex

@Article{MakNNMA14,
  author  = {Rachel Mak and Mirna Lerotic and Holger Fleckenstein and Stefan Vogt and Stefan M. Wild and Sven Leyffer and Yefim Sheynkin and Chris Jacobsen},
  title   = {Non-Negative Matrix Analysis for Effective Feature Extraction in {X-ray} Spectromicroscopy},
  doi     = {10.1039/C4FD00023D},
  pages   = {357--371},
  volume  = {171},
  journal = {Faraday Discussions},
  year    = {2014},
}

Multi-Objective Optimization of HPC Kernels for Performance, Power, and Energy. Balaprakash, P.; Tiwari, A.; and Wild, S. M. In Jarvis, S. A.; Wright, S. A.; and Hammond, S. D., editor(s), High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation, volume 8551, pages 239–260, 2014. Springer
doi link bibtex

@InProceedings{Multiobj13,
  author    = {Prasanna Balaprakash and Ananta Tiwari and Stefan M. Wild},
  booktitle = {High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation},
  title     = {Multi-Objective Optimization of {HPC} Kernels for Performance, Power, and Energy},
  doi       = {10.1007/978-3-319-10214-6_12},
  editor    = {Jarvis, Stephen A. and Wright, Steven A. and Hammond, Simon D.},
  pages     = {239--260},
  publisher = {Springer},
  volume    = {8551},
  anote     = {Proceedings of the 4th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS13)},
  aseries   = {Lecture Notes in Computer Science},
  mnote     = {P4069-0413},
  year      = {2014},
}

Nuclear Energy Density Optimization: Shell Structure. Kortelainen, M.; McDonnell, J. D.; Nazarewicz, W.; Olsen, E.; Reinhard, P.; Sarich, J.; Schunck, N.; Wild, S. M.; Davesne, D.; Erler, J.; and Pastore, A. Physical Review C, 89(5): 054314. 2014.
doi link bibtex

@Article{UNEDF2,
  author  = {M. Kortelainen and J. D. McDonnell and W. Nazarewicz and E. Olsen and P.-G. Reinhard and J. Sarich and N. Schunck and S. M. Wild and D. Davesne and J. Erler and A. Pastore},
  title   = {Nuclear Energy Density Optimization: Shell Structure},
  doi     = {10.1103/PhysRevC.89.054314},
  number  = {5},
  pages   = {054314},
  volume  = {89},
  journal = {Physical Review C},
  year    = {2014},
}

Do You Trust Derivatives or Differences?. Moré, J. J.; and Wild, S. M. Journal of Computational Physics, 273: 268–277. 2014.
doi link bibtex

@Article{more2014nd,
  author  = {Jorge J. Mor\'e and Stefan M. Wild},
  title   = {Do You Trust Derivatives or Differences?},
  doi     = {10.1016/j.jcp.2014.04.056},
  pages   = {268--277},
  volume  = {273},
  gurl    = {https://scholar.google.com/scholar?cluster=16936783637629538358},
  journal = {Journal of Computational Physics},
  year    = {2014},
}

2013 (12)

Framework for Optimizing Power, Energy, and Performance (Poster). Balaprakash, P.; Tiwari, A.; and Wild, S. M. In International Conference for High Performance Computing, Networking, Storage, and Analysis (SC13), 2013.

Framework for Optimizing Power, Energy, and Performance (Poster) [link]

Paper link bibtex

@InProceedings{PBATSW13poster,
  author    = {Prasanna Balaprakash and Ananta Tiwari and Stefan M. Wild},
  booktitle = {International Conference for High Performance Computing, Networking, Storage, and Analysis (SC13)},
  title     = {Framework for Optimizing Power, Energy, and Performance (Poster)},
  url       = {http://sc13.supercomputing.org/sites/default/files/PostersArchive/post154.html},
  year      = {2013},
}

Unsupervised Cell Identification on Multidimensional X-ray Fluorescence Datasets. Wang, S.; Ward, J.; Leyffer, S.; Wild, S. M.; Jacobsen, C.; and Vogt, S. In ACM SIGGRAPH 2013 Posters, pages 88:1, 2013.
doi link bibtex

@InProceedings{Wangposter13,
  author    = {Siwei Wang and Jesse Ward and Sven Leyffer and Stefan M. Wild and Chris Jacobsen and Stefan Vogt},
  booktitle = {ACM SIGGRAPH 2013 Posters},
  title     = {Unsupervised Cell Identification on Multidimensional {X-ray} Fluorescence Datasets},
  doi       = {10.1145/2503385.2503481},
  pages     = {88:1},
  year      = {2013},
}

Active-Learning-Based Surrogate Models for Empirical Performance Tuning. Balaprakash, P.; Gramacy, R. B.; and Wild, S. M. In Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2013), pages 1–8, 2013.
doi link bibtex

@InProceedings{PBRGSW13,
  author    = {Prasanna Balaprakash and Robert B. Gramacy and Stefan M. Wild},
  booktitle = {Proceedings of IEEE International Conference on Cluster Computing (CLUSTER 2013)},
  title     = {Active-Learning-Based Surrogate Models for Empirical Performance Tuning},
  doi       = {10.1109/CLUSTER.2013.6702683},
  pages     = {1--8},
  year      = {2013},
}

An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning. Balaprakash, P.; Wild, S. M.; and Hovland, P. D. In High Performance Computing for Computational Science - VECPAR 2012, 10th International Conference, Kobe, Japan, July 17-20, 2012, Revised Selected Papers, volume 7851, of Lecture Notes in Computer Science, pages 261–269, 2013. Springer
doi link bibtex

@InProceedings{PBSWPHLNCS13,
  author    = {Prasanna Balaprakash and Stefan M. Wild and Paul D. Hovland},
  booktitle = {High Performance Computing for Computational Science - VECPAR 2012, 10th International Conference, Kobe, Japan, July 17-20, 2012, Revised Selected Papers},
  title     = {An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning},
  doi       = {10.1007/978-3-642-38718-0_26},
  pages     = {261--269},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {7851},
  editors   = {M. J. Dayd\'e, O. Marques, K. Nakajima},
  misbn     = {978-3-642-38717-3},
  year      = {2013},
}

Axially Deformed Solution of the Skyrme-Hartree-Fock-Bogolyubov Equations Using the Transformed Harmonic Oscillator Basis (II) HFBTHO v2.00d: A New Version of the Program. Stoitsov, M. V.; Schunck, N.; Kortelainen, M.; Michel, N.; Nam, H.; Olsen, E.; Sarich, J.; and Wild, S. M. Computer Physics Communications, 184(6): 1592–1604. 2013.
doi link bibtex

@Article{HFBTHOv2,
  author  = {M. V. Stoitsov and N. Schunck and M. Kortelainen and N. Michel and H. Nam and E. Olsen and J. Sarich and S. M. Wild},
  title   = {Axially Deformed Solution of the {Skyrme-Hartree-Fock-Bogolyubov} Equations Using the Transformed Harmonic Oscillator Basis {(II) HFBTHO} v2.00d: {A} New Version of the Program},
  doi     = {10.1016/j.cpc.2013.01.013},
  number  = {6},
  pages   = {1592--1604},
  volume  = {184},
  journal = {Computer Physics Communications},
  year    = {2013},
}

Non-Intrusive Termination of Noisy Optimization. Larson, J.; and Wild, S. M. Optimization Methods and Software, 28(5): 993–1011. 2013.
doi link bibtex

@Article{JLSW13,
  author  = {Jeffrey Larson and Stefan M. Wild},
  title   = {Non-Intrusive Termination of Noisy Optimization},
  doi     = {10.1080/10556788.2012.656116},
  number  = {5},
  pages   = {993--1011},
  volume  = {28},
  journal = {Optimization Methods and Software},
  year    = {2013},
}

Computational Nuclear Quantum Many-Body Problem: The UNEDF Project. Bogner, S.; Bulgac, A.; Carlson, J.; Enge, J.; Fann, G.; Furnstahl, R. J.; Gandolfi, S.; Hagen, G.; Horoi, M.; Johnson, C.; Kortelainen, M.; Lusk, E.; Maris, P.; Nam, H.; Navratil, P.; Nazarewicz, W.; Ng, E. G.; Nobre, G. P. A.; Ormand, E.; Papenbrock, T.; Pei, J. C.; Pieper, S. C.; Quaglioni, S.; Roche, K. J.; Sarich, J.; Schunck, N.; Sosonkina, M.; Terasaki, J.; Thompson, I.; Vary, J. P.; and Wild, S. M. Computer Physics Communications, 184(10): 2235–2250. 2013.
doi link bibtex

@Article{UNEDF13,
  author  = {S. Bogner and A. Bulgac and J. Carlson and J. Enge and G. Fann and R. J. Furnstahl and S. Gandolfi and G. Hagen and M. Horoi and C. Johnson and M. Kortelainen and E. Lusk and P. Maris and H. Nam and P. Navratil and W. Nazarewicz and E. G. Ng and G. P. A. Nobre and E. Ormand and T. Papenbrock and J. C. Pei and S. C. Pieper and S. Quaglioni and K. J. Roche and J. Sarich and N. Schunck and M. Sosonkina and J. Terasaki and I. Thompson and J. P. Vary and S. M. Wild},
  title   = {Computational Nuclear Quantum Many-Body Problem: {The UNEDF} Project},
  doi     = {10.1016/j.cpc.2013.05.020},
  number  = {10},
  pages   = {2235--2250},
  volume  = {184},
  journal = {Computer Physics Communications},
  notes2  = {arXiv:1304.3713},
  year    = {2013},
}

Development of a Fast, Robust Numerical Tool for the Design, Optimization, and Control of IC Engines. Aithal, S. M.; and Wild, S. M. In Proceedings of the SAE 11th International Conference on Engines & Vehicles, 2013.
doi link bibtex

@InProceedings{SASW13,
  author     = {Shashi M. Aithal and Stefan M. Wild},
  booktitle  = {Proceedings of the SAE 11th International Conference on Engines \& Vehicles},
  title      = {Development of a Fast, Robust Numerical Tool for the Design, Optimization, and Control of {IC} Engines},
  doi        = {10.4271/2013-24-0141},
  anote      = {SAE Technical Paper 2013-24-0141},
  apublisher = {SAE},
  year       = {2013},
}

Optimized Chiral Nucleon-Nucleon Interaction at Next-to-Next-to-Leading Order. Ekström, A.; Baardsen, G.; Forssén, C.; Hagen, G.; Hjorth-Jensen, M.; Jansen, G. R.; Machleidt, R.; Nazarewicz, W.; Papenbrock, T.; Sarich, J.; and Wild, S. M. Physical Review Letters, 110(19): 192502. 2013.
doi link bibtex

@Article{Ekstrom13,
  author  = {Ekstr\"om, A. and Baardsen, G. and Forss\'en, C. and Hagen, G. and Hjorth-Jensen, M. and Jansen, G. R. and Machleidt, R. and Nazarewicz, W. and Papenbrock, T. and Sarich, J. and Wild, S. M.},
  title   = {Optimized Chiral Nucleon-Nucleon Interaction at Next-to-Next-to-Leading Order},
  doi     = {10.1103/PhysRevLett.110.192502},
  number  = {19},
  pages   = {192502},
  volume  = {110},
  journal = {Physical Review Letters},
  year    = {2013},
}

Novel Process to Use Vehicle Simulations Directly as Inputs to the VOLPE Model. Moawad, A.; Halbach, S.; Pagerit, S.; Rousseau, A.; Balaprakash, P.; and Wild, S. M. Technical Report ANL/ESD-13/13, Argonne National Laboratory, 2013.

Novel Process to Use Vehicle Simulations Directly as Inputs to the VOLPE Model [pdf]

Paper link bibtex

@TechReport{DOT13,
  author      = {Ayman Moawad and Shane Halbach and Sylvain Pagerit and Aymeric Rousseau and Prasanna Balaprakash and Stefan M. Wild},
  institution = {Argonne National Laboratory},
  title       = {Novel Process to Use Vehicle Simulations Directly as Inputs to the {VOLPE} Model},
  number      = {ANL/ESD-13/13},
  type        = {Technical Memorandum},
  url         = {https://www.safercar.gov/staticfiles/rulemaking/pdf/cafe/ANL-VOLPE_Novel_Process-Simulations-as-inputs_1311.pdf},
  year        = {2013},
}

Variable Selection and Sensitivity Analysis via Dynamic Trees with an Application to Computer Code Performance Tuning. Gramacy, R. B.; Taddy, M. A.; and Wild, S. M. Annals of Applied Statistics, 7(1): 51–80. 2013.
doi link bibtex

@Article{GraTadWil2013,
  author  = {Robert B. Gramacy and Matthew A. Taddy and Stefan M. Wild},
  title   = {Variable Selection and Sensitivity Analysis via Dynamic Trees with an Application to Computer Code Performance Tuning},
  doi     = {10.1214/12-AOAS590},
  number  = {1},
  pages   = {51--80},
  volume  = {7},
  journal = {Annals of Applied Statistics},
  year    = {2013},
}

Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization. Wild, S. M.; and Shoemaker, C. A. SIAM Review, 55(2): 349–371. 2013.
doi link bibtex

@Article{SMWCAS13,
  author  = {Stefan M. Wild and Christine A. Shoemaker},
  title   = {Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization},
  doi     = {10.1137/120902434},
  number  = {2},
  pages   = {349--371},
  volume  = {55},
  gurl    = {https://scholar.google.com/scholar?cluster=12113131005455194886},
  journal = {SIAM Review},
  year    = {2013},
}

2012 (10)

SPAPT: Search Problems in Automatic Performance Tuning. Balaprakash, P.; Wild, S. M.; and Norris, B. Procedia Computer Science (ICCS 2012), 9: 1959–1968. 2012.
doi link bibtex

@Article{PBSWBN11,
  author  = {Prasanna Balaprakash and Stefan M. Wild and Boyana Norris},
  title   = {{SPAPT:} {Search} Problems in Automatic Performance Tuning},
  doi     = {10.1016/j.procs.2012.04.214},
  pages   = {1959--1968},
  volume  = {9},
  anote   = {In Proceedings of the International Conference on Computational Science, ICCS 2012},
  journal = {Procedia Computer Science (ICCS 2012)},
  year    = {2012},
}

Quality Input for Microscopic Fission Theory. Nazarewicz, W.; Schunck, N.; and Wild, S. M. Stockpile Stewardship Quarterly, 2(1). 2012.
link bibtex

@Article{WNNSSW12,
  author  = {Witold Nazarewicz and Nicolas Schunck and Stefan M. Wild},
  title   = {Quality Input for Microscopic Fission Theory},
  number  = {1},
  volume  = {2},
  aurl    = {http://nuclei.mps.ohio-state.edu/content/highlights/UNEDF/unedf1.pdf},
  journal = {Stockpile Stewardship Quarterly},
  year    = {2012},
}

Estimating Derivatives of Noisy Simulations. Moré, J. J.; and Wild, S. M. ACM Transactions on Mathematical Software, 38(3): 19:1–19:21. 2012.
doi link bibtex

@Article{more2011edn,
  author  = {Jorge J. Mor{\'e} and Stefan M. Wild},
  title   = {Estimating Derivatives of Noisy Simulations},
  doi     = {10.1145/2168773.2168777},
  number  = {3},
  pages   = {19:1--19:21},
  volume  = {38},
  gurl    = {https://scholar.google.com/scholar?cluster=11200403943296784554},
  journal = {ACM Transactions on Mathematical Software},
  year    = {2012},
}

Occupation Number-based Energy Functional for Nuclear Masses. Bertolli, M. G.; Papenbrock, T.; and Wild, S. M. Physical Review C, 85(1): 014322. 2012.
doi link bibtex

@Article{BPW11,
  author  = {M. G. Bertolli and T. Papenbrock and S. M. Wild},
  title   = {Occupation Number-based Energy Functional for Nuclear Masses},
  doi     = {10.1103/PhysRevC.85.014322},
  number  = {1},
  pages   = {014322},
  volume  = {85},
  journal = {Physical Review C},
  year    = {2012},
}

Report on the Workshop on Extreme-Scale Solvers: Transition to Future Architectures. Ang, J.; Evans, K.; Geist, A.; Heroux, M.; Hovland, P. D.; Marques, O.; Curfman McInnes, L.; Ng, E. G.; and Wild, S. M. Technical Report U.S.\ Department of Energy, ASCR, 2012.

Report on the Workshop on Extreme-Scale Solvers: Transition to Future Architectures [pdf]

Paper link bibtex

@TechReport{Angetal:12,
  author      = {James Ang and Katherine Evans and Al Geist and Michael Heroux and Paul D. Hovland and Osni Marques and Lois {Curfman McInnes} and Esmond G. Ng and Stefan M. Wild},
  institution = {U.S.\ Department of Energy, ASCR},
  title       = {Report on the Workshop on Extreme-Scale Solvers: Transition to Future Architectures},
  type        = {Report},
  url         = {https://science.osti.gov/-/media/ascr/pdf/program-documents/docs/reportExtremeScaleSolvers2012.pdf},
  year        = {2012},
}

The TAO Linearly Constrained Augmented Lagrangian Method for PDE-Constrained Optimization. Gawlik, E.; Munson, T.; Sarich, J.; and Wild, S. M. Technical Report ANL/MCS-P2003-0112, Argonne National Laboratory, MCS Division, 2012.

The TAO Linearly Constrained Augmented Lagrangian Method for PDE-Constrained Optimization [pdf]

Paper link bibtex

@TechReport{Gawlik12,
  author      = {Evan Gawlik and Todd Munson and Jason Sarich and Stefan M. Wild},
  institution = {Argonne National Laboratory, MCS Division},
  title       = {The {TAO} Linearly Constrained Augmented {Lagrangian} Method for {PDE}-Constrained Optimization},
  number      = {ANL/MCS-P2003-0112},
  url         = {http://www.mcs.anl.gov/uploads/cels/papers/P2003-0112.pdf},
  year        = {2012},
}

Benefits of Deeper Analysis in Simulation-based Groundwater Optimization Problems. Kannan, A.; and Wild, S. M. In Proceedings of the XIX International Conference on Computational Methods in Water Resources (CMWR 2012), 2012.

Benefits of Deeper Analysis in Simulation-based Groundwater Optimization Problems [pdf]

2

Paper link bibtex

@InProceedings{AKSW12,
  author    = {Aswin Kannan and Stefan M. Wild},
  booktitle = {Proceedings of the XIX International Conference on Computational Methods in Water Resources (CMWR 2012)},
  title     = {Benefits of Deeper Analysis in Simulation-based Groundwater Optimization Problems},
  url       = {http://www.mcs.anl.gov/~wild/papers/2012/AKSW12.pdf},
  url2      = {http://cmwr2012.cee.illinois.edu/Papers/Special%20Sessions/Optimization%20and%20Uncertainty%20Analysis%20of%20Water%20Resources%20from%20a%20Systems%20Perspective/Kannan.Aswin.pdf},
  year      = {2012},
}

TAO 2.0 Users Manual. Munson, T.; Sarich, J.; Wild, S. M.; Benson, S.; and Curfman McInnes, L. Technical Report ANL/MCS-TM-322, Argonne National Laboratory, 2012.

Paper link bibtex

@TechReport{tao-man,
  author      = {Todd Munson and Jason Sarich and Stefan M. Wild and Steve Benson and Lois {Curfman McInnes}},
  institution = {Argonne National Laboratory},
  title       = {{TAO} 2.0 Users Manual},
  number      = {ANL/MCS-TM-322},
  type        = {Technical Memorandum},
  url         = {http://www.mcs.anl.gov/uploads/cels/papers/ANL-MCS-TM-322.pdf},
  year        = {2012},
}

Nuclear Energy Density Optimization: Large Deformations. Kortelainen, M.; McDonnell, J. D.; Nazarewicz, W.; Reinhard, P.; Sarich, J.; Schunck, N.; Stoitsov, M. V.; and Wild, S. M. Physical Review C, 85: 024304. 2012.
doi link bibtex

@Article{UNEDF1,
  author  = {M. Kortelainen and J. D. McDonnell and W. Nazarewicz and P.-G. Reinhard and J. Sarich and N. Schunck and M. V. Stoitsov and S. M. Wild},
  title   = {Nuclear Energy Density Optimization: Large Deformations},
  doi     = {10.1103/PhysRevC.85.024304},
  pages   = {024304},
  volume  = {85},
  journal = {Physical Review C},
  year    = {2012},
}

UNEDF: Advanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem. Nam, H.; Stoitsov, M. V.; Nazarewicz, W.; Bulgac, A.; Hagen, G.; Kortelainen, M.; Maris, P.; Pei, J. C.; Roche, K. J.; Schunck, N.; Thompson, I.; Vary, J. P.; and Wild, S. M. Journal of Physics: Conference Series, 402: 012033. 2012.

UNEDF: Advanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem [link]

2 doi link bibtex

@Article{Nam12,
  author  = {H. Nam and M. V. Stoitsov and W. Nazarewicz and A. Bulgac and G. Hagen and M. Kortelainen and P. Maris and J. C. Pei and K. J. Roche and N. Schunck and I. Thompson and J. P. Vary and Stefan M. Wild},
  title   = {{UNEDF: A}dvanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem},
  doi     = {10.1088/1742-6596/402/1/012033},
  pages   = {012033},
  volume  = {402},
  journal = {Journal of Physics: Conference Series},
  notes   = {Proceedings for Conference on Computational Physics (CCP2011)},
  url2    = {http://arxiv.org/abs/1205.0227},
  year    = {2012},
}

2011 (7)

Advancing Nuclear Physics Through TOPS Solvers and Tools. Ng, E. G.; Sarich, J.; Munson, T.; Wild, S. M.; Aktulga, H.; Yang, C.; Maris, P.; Vary, J. P.; Kortelainen, M.; Nazarewicz, W.; Papenbrock, T.; Schunck, N.; Stoitsov, M. V.; and Bertolli, M. G. In Proceedings of SciDAC 2011, 2011.

Advancing Nuclear Physics Through TOPS Solvers and Tools [pdf]

Paper link bibtex

@InProceedings{NgSciDAC11,
  author    = {E. G. Ng and J. Sarich and T. Munson and S. M. Wild and H. Aktulga and C. Yang and P. Maris and J. P. Vary and M. Kortelainen and W. Nazarewicz and T. Papenbrock and N. Schunck and M. V. Stoitsov and M. G. Bertolli},
  booktitle = {Proceedings of SciDAC 2011},
  title     = {Advancing Nuclear Physics Through {TOPS} Solvers and Tools},
  url       = {http://www.mcs.anl.gov/uploads/cels/papers/scidac11/final/NgEsmond.pdf},
  year      = {2011},
}

Obtaining Quadratic Models of Noisy Functions. Kannan, A.; and Wild, S. M. Technical Report ANL/MCS-P1975-1111, Argonne National Laboratory, MCS Division, 2011.

Obtaining Quadratic Models of Noisy Functions [pdf]

Paper link bibtex

@TechReport{AKSW11,
  author      = {Aswin Kannan and Stefan M. Wild},
  institution = {Argonne National Laboratory, MCS Division},
  title       = {Obtaining Quadratic Models of Noisy Functions},
  number      = {ANL/MCS-P1975-1111},
  url         = {http://www.mcs.anl.gov/uploads/cels/papers/P1975-1111.pdf},
  year        = {2011},
}

Can Search Algorithms Save Large-Scale Automatic Performance Tuning?. Balaprakash, P.; Wild, S. M.; and Hovland, P. D. Procedia Computer Science (ICCS 2011), 4: 2136–2145. 2011.
doi link bibtex

@Article{Balaprakash20112136,
  author  = {Prasanna Balaprakash and Stefan M. Wild and Paul D. Hovland},
  title   = {Can Search Algorithms Save Large-Scale Automatic Performance Tuning?},
  doi     = {10.1016/j.procs.2011.04.234},
  pages   = {2136--2145},
  volume  = {4},
  journal = {Procedia Computer Science (ICCS 2011)},
  year    = {2011},
}

UNEDF: Advanced Scientific Computing Transforms the Low-Energy Nuclear Many-Body Problem. Stoitsov, M. V.; Nam, H.; Nazarewicz, W.; Bulgac, A.; Hagen, G.; Kortelainen, M.; Pei, J. C.; Roche, K. J.; Schunck, N.; Thompson, I.; Vary, J. P.; and Wild, S. M. In Proceedings of SciDAC 2011, 2011.

UNEDF: Advanced Scientific Computing Transforms the Low-Energy Nuclear Many-Body Problem [pdf]

Paper link bibtex

@InProceedings{StoitsovSciDAC11,
  author    = {M. V. Stoitsov and H. Nam and W. Nazarewicz and A. Bulgac and G. Hagen and M. Kortelainen and J. C. Pei and K. J. Roche and N. Schunck and I. Thompson and J. P. Vary and S. M. Wild},
  booktitle = {Proceedings of SciDAC 2011},
  title     = {{UNEDF}: Advanced Scientific Computing Transforms the Low-Energy Nuclear Many-Body Problem},
  url       = {http://www.mcs.anl.gov/uploads/cels/papers/scidac11/final/Stoitsov_scidac2011.pdf},
  year      = {2011},
}

Computing Heavy Elements. Schunck, N.; Baran, A.; Kortelainen, M.; McDonnell, J. D.; Moré, J. J.; Nazarewicz, W.; Pei, J. C.; Sarich, J.; Sheikh, J.; Staszczak, A.; Stoitsov, M. V.; and Wild, S. M. In Proceedings of SciDAC 2011, 2011.

Paper link bibtex

@InProceedings{SchunckSciDAC11,
  author    = {N. Schunck and A. Baran and M. Kortelainen and J. D. McDonnell and J. J. Mor\'e and W. Nazarewicz and J. C. Pei and J. Sarich and J. Sheikh and A. Staszczak and M. V. Stoitsov and S. M. Wild},
  booktitle = {Proceedings of SciDAC 2011},
  title     = {Computing Heavy Elements},
  url       = {http://www.mcs.anl.gov/uploads/cels/papers/scidac11/final/Schunck.scidac04a.pdf},
  year      = {2011},
}

Estimating Computational Noise. Moré, J. J.; and Wild, S. M. SIAM Journal on Scientific Computing, 33(3): 1292–1314. 2011.
doi link bibtex

@Article{more2011ecn,
  author  = {Jorge J. Mor{\'e} and Stefan M. Wild},
  title   = {Estimating Computational Noise},
  doi     = {10.1137/100786125},
  number  = {3},
  pages   = {1292--1314},
  volume  = {33},
  gurl    = {https://scholar.google.com/scholar?cluster=17340995807610168622},
  journal = {SIAM Journal on Scientific Computing},
  year    = {2011},
}

Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms. Wild, S. M.; and Shoemaker, C. A. SIAM Journal on Optimization, 21(3): 761–781. 2011.
doi link bibtex

@Article{SMWCAS11,
  author  = {Stefan M. Wild and Christine A. Shoemaker},
  title   = {Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms},
  doi     = {10.1137/09074927X},
  number  = {3},
  pages   = {761--781},
  volume  = {21},
  gurl    = {https://scholar.google.com/scholar?cluster=12118663721886734692},
  journal = {SIAM Journal on Optimization},
  year    = {2011},
}

2010 (1)

Nuclear Energy Density Optimization. Kortelainen, M.; Lesinski, T.; Moré, J. J.; Nazarewicz, W.; Sarich, J.; Schunck, N.; Stoitsov, M. V.; and Wild, S. M. Physical Review C, 82(2): 024313. 2010.
doi link bibtex

@Article{UNEDF0,
  author  = {M. Kortelainen and T. Lesinski and J. J. Mor{\'e} and W. Nazarewicz and J. Sarich and N. Schunck and M. V. Stoitsov and S. M. Wild},
  title   = {Nuclear Energy Density Optimization},
  doi     = {10.1103/PhysRevC.82.024313},
  number  = {2},
  pages   = {024313},
  volume  = {82},
  journal = {Physical Review C},
  year    = {2010},
}

2009 (2)

Towards The Universal Nuclear Energy Density Functional. Stoitsov, M. V.; Moré, J. J.; Nazarewicz, W.; Pei, J. C.; Sarich, J.; Schunck, N.; Staszczak, A.; and Wild, S. M. Journal of Physics: Conference Series, 180: 012082. 2009.
doi link bibtex

@Article{SciDAC09,
  author  = {M. V. Stoitsov and J. J. Mor\'e and W. Nazarewicz and J. C. Pei and J. Sarich and N. Schunck and A. Staszczak and S. M. Wild},
  title   = {Towards The Universal Nuclear Energy Density Functional},
  doi     = {10.1088/1742-6596/180/1/012082},
  pages   = {012082},
  volume  = {180},
  journal = {Journal of Physics: Conference Series},
  year    = {2009},
}

Benchmarking Derivative-Free Optimization Algorithms. Moré, J. J.; and Wild, S. M. SIAM Journal on Optimization, 20(1): 172–191. 2009.
doi link bibtex

@Article{JJMSMW09,
  author  = {Jorge J. Mor{\'e} and Stefan M. Wild},
  title   = {Benchmarking Derivative-Free Optimization Algorithms},
  doi     = {10.1137/080724083},
  number  = {1},
  pages   = {172--191},
  volume  = {20},
  gurl    = {https://scholar.google.com/scholar?cluster=3053803390196460065},
  journal = {SIAM Journal on Optimization},
  year    = {2009},
}

2008 (4)

MNH: A Derivative-Free Optimization Algorithm Using Minimal Norm Hessians. Wild, S. M. In Tenth Copper Mountain Conference on Iterative Methods, 2008.

MNH: A Derivative-Free Optimization Algorithm Using Minimal Norm Hessians [pdf]

Paper link bibtex

@InProceedings{SW08,
  author    = {Stefan M. Wild},
  booktitle = {Tenth Copper Mountain Conference on Iterative Methods},
  title     = {{MNH: A} Derivative-Free Optimization Algorithm Using Minimal Norm {Hessians}},
  url       = {http://grandmaster.colorado.edu/~copper/2008/SCWinners/Wild.pdf},
  gurl      = {https://scholar.google.com/scholar?cluster=6407907761614456217},
  year      = {2008},
}

Derivative-Free Optimization Algorithms for Computationally Expensive Functions. Wild, S. M. Ph.D. Thesis, Cornell University, 2008.

Derivative-Free Optimization Algorithms for Computationally Expensive Functions [link]

Paper link bibtex

@PhdThesis{WildPhD,
  author = {Stefan M. Wild},
  title  = {Derivative-Free Optimization Algorithms for Computationally Expensive Functions},
  url    = {http://ecommons.cornell.edu/handle/1813/11248},
  gurl   = {https://scholar.google.com/scholar?cluster=17517080034170507117},
  school = {Cornell University},
  year   = {2008},
}

Bayesian Calibration of Computationally Expensive Models Using Optimization and Radial Basis Function Approximation. Bliznyuk, N.; Ruppert, D.; Shoemaker, C. A.; Regis, R. G.; Wild, S. M.; and Mugunthan, P. Journal of Computational and Graphical Statistics, 17(2): 270–294. 2008.
doi link bibtex

@Article{BLIZNYUK08,
  author  = {Nikolay Bliznyuk and David Ruppert and Christine A. Shoemaker and Rommel G. Regis and Stefan M. Wild and Pradeep Mugunthan},
  title   = {Bayesian Calibration of Computationally Expensive Models Using Optimization and Radial Basis Function Approximation},
  doi     = {10.1198/106186008X320681},
  number  = {2},
  pages   = {270--294},
  volume  = {17},
  journal = {Journal of Computational and Graphical Statistics},
  year    = {2008},
}

ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions. Wild, S. M.; Regis, R. G.; and Shoemaker, C. A. SIAM Journal on Scientific Computing, 30(6): 3197–3219. 2008.
doi link bibtex

@Article{SWRRCS07,
  author  = {Stefan M. Wild and Rommel G. Regis and Christine A. Shoemaker},
  title   = {{ORBIT:} {O}ptimization by Radial Basis Function Interpolation in Trust-Regions},
  doi     = {10.1137/070691814},
  number  = {6},
  pages   = {3197--3219},
  volume  = {30},
  gurl    = {https://scholar.google.com/scholar?cluster=784259722464605159},
  journal = {SIAM Journal on Scientific Computing},
  year    = {2008},
}

2007 (1)

Maximizing Influence in a Competitive Social Network: A Follower's Perspective. Carnes, T.; Nagarajan, C.; Wild, S. M.; and van Zuylen, A. In ICEC '07: Proceedings of the Ninth International Conference on Electronic Commerce, pages 351–360, 2007. ACM
doi link bibtex

@InProceedings{TCCNSMWAvZ07,
  author    = {Tim Carnes and Chandrashekhar Nagarajan and Stefan M. Wild and Anke van Zuylen},
  booktitle = {ICEC '07: Proceedings of the Ninth International Conference on Electronic Commerce},
  title     = {Maximizing Influence in a Competitive Social Network: {A} Follower's Perspective},
  doi       = {10.1145/1282100.1282167},
  pages     = {351--360},
  publisher = {ACM},
  year      = {2007},
}

2004 (1)

Improving Non-Negative Matrix Factorizations Through Structured Initialization. Wild, S. M.; Curry, J. H.; and Dougherty, A. Pattern Recognition, 37(11): 2217–2232. 2004.
doi link bibtex

@Article{SWJCAD04,
  author  = {Stefan M. Wild and James H. Curry and Anne Dougherty},
  title   = {Improving Non-Negative Matrix Factorizations Through Structured Initialization},
  doi     = {10.1016/j.patcog.2004.02.013},
  number  = {11},
  pages   = {2217--2232},
  volume  = {37},
  journal = {Pattern Recognition},
  year    = {2004},
}

2003 (2)

Seeding Non-Negative Matrix Factorizations with the Spherical K-Means Clustering. Wild, S. M. Master's thesis, University of Colorado, 2003.

Seeding Non-Negative Matrix Factorizations with the Spherical K-Means Clustering [link]

Paper link bibtex

@MastersThesis{WildMS,
  author = {Stefan M. Wild},
  title  = {Seeding Non-Negative Matrix Factorizations with the Spherical K-Means Clustering},
  url    = {http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.88.1623},
  school = {University of Colorado},
  year   = {2003},
}

Motivating Non-Negative Matrix Factorizations. Wild, S. M.; Curry, J. H.; and Dougherty, A. In Proceedings of the Eighth SIAM Conference on Applied Linear Algebra, 2003.

Motivating Non-Negative Matrix Factorizations [pdf]

Paper link bibtex

@InProceedings{SWJCAD03,
  author    = {Stefan M. Wild and James H. Curry and Anne Dougherty},
  booktitle = {Proceedings of the Eighth SIAM Conference on Applied Linear Algebra},
  title     = {Motivating Non-Negative Matrix Factorizations},
  url       = {http://www.siam.org/meetings/la03/proceedings/WILDstef.pdf},
  year      = {2003},
}

2002 (1)

Probabilistically Optimized Airline Overbooking Strategies, or ``Anyone Willing to Take a Later Flight?!". Leder, K. Z.; Spagnolie, S. E.; and Wild, S. M. Journal of Undergraduate Mathematics and Its Applications, 23(3): 317–338. 2002.

Probabilistically Optimized Airline Overbooking Strategies, or ``Anyone Willing to Take a Later Flight?!" [link]

Paper link bibtex

@Article{KLSSSW02,
  author  = {Kevin Z. Leder and Saverio E. Spagnolie and Stefan M. Wild},
  title   = {Probabilistically Optimized Airline Overbooking Strategies, or ``{A}nyone Willing to Take a Later Flight?!"},
  number  = {3},
  pages   = {317--338},
  url     = {http://www.comap.com/product/periodicals/index.html},
  volume  = {23},
  journal = {Journal of Undergraduate Mathematics and Its Applications},
  year    = {2002},
}