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\n \n \n Fix it now\n

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\n  \n 2026\n \n \n (8)\n \n \n
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\n \n\n \n \n \n \n \n \n ReMU: Regional Minimal Updating for Model-Based Derivative-Free Optimization.\n \n \n \n \n\n\n \n Xie, P.; and Wild, S. M.\n\n\n \n\n\n\n Optimization Methods and Software,1–30. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"ReMU:Paper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-wild-2026-remu,\n  author  = {Pengcheng Xie and Stefan M. Wild},\n  title   = {{ReMU}: Regional Minimal Updating for Model-Based Derivative-Free Optimization},\n  journal = {Optimization Methods and Software},\n  year    = {2026},\n  pages   = {1--30},\n  doi     = {10.1080/10556788.2026.2660368},\n  url     = {https://doi.org/10.1080/10556788.2026.2660368},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Least $H^2$ Norm Updating of Quadratic Interpolation Models for Derivative-Free Trust-Region Algorithms.\n \n \n \n \n\n\n \n Xie, P.; and Yuan, Y.\n\n\n \n\n\n\n IMA Journal of Numerical Analysis, 46(1): 21–50. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"LeastPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-yuan-2026-h2-updating,\n  author  = {Pengcheng Xie and Ya-xiang Yuan},\n  title   = {Least {$H^2$} Norm Updating of Quadratic Interpolation Models for Derivative-Free Trust-Region Algorithms},\n  journal = {IMA Journal of Numerical Analysis},\n  year    = {2026},\n  volume  = {46},\n  number  = {1},\n  pages   = {21--50},\n  doi     = {10.1093/imanum/drae106},\n  url     = {https://doi.org/10.1093/imanum/drae106},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n A New Two-Dimensional Model-Based Subspace Method for Large-Scale Unconstrained Derivative-Free Optimization: 2D-MoSub.\n \n \n \n \n\n\n \n Xie, P.; and Yuan, Y.\n\n\n \n\n\n\n Optimization Methods and Software, 41(1): 118–150. 2026.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-yuan-2026-2d-mosub,\n  author  = {Pengcheng Xie and Ya-xiang Yuan},\n  title   = {A New Two-Dimensional Model-Based Subspace Method for Large-Scale Unconstrained Derivative-Free Optimization: {2D-MoSub}},\n  journal = {Optimization Methods and Software},\n  year    = {2026},\n  volume  = {41},\n  number  = {1},\n  pages   = {118--150},\n  doi     = {10.1080/10556788.2025.2601670},\n  url     = {https://doi.org/10.1080/10556788.2025.2601670},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Second-order $H^1$-norm Error Analysis for Time-Fractional Advection-Dispersion Equations Based on the Fast Averaged L1 Method.\n \n \n \n \n\n\n \n Huang, L.; Li, L.; and Xie, P.\n\n\n \n\n\n\n 2026.\n \n\n\n\n
\n\n\n\n \n \n \"Second-orderPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{huang-li-xie-2026-h1-time-fractional,\n  author        = {Liangcai Huang and Lin Li and Pengcheng Xie},\n  title         = {Second-order {$H^1$}-norm Error Analysis for Time-Fractional Advection-Dispersion Equations Based on the Fast Averaged {L1} Method},\n  year          = {2026},\n  eprint        = {2606.22083},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.NA},\n  url           = {https://arxiv.org/abs/2606.22083},\n  keywords      = {numerical PDE}\n}\n\n
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\n \n\n \n \n \n \n \n \n MATRO: Metric-Aware Fully Quadratic Trust Regions for Derivative-Free Optimization.\n \n \n \n \n\n\n \n Hu, W.; Xie, P.; Yuan, Y.; and Zhang, L.\n\n\n \n\n\n\n 2026.\n \n\n\n\n
\n\n\n\n \n \n \"MATRO:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{hu-xie-yuan-zhang-2026-matro,\n  author        = {Wei Hu and Pengcheng Xie and Ya-xiang Yuan and Li Zhang},\n  title         = {{MATRO}: Metric-Aware Fully Quadratic Trust Regions for Derivative-Free Optimization},\n  year          = {2026},\n  eprint        = {2605.30845},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2605.30845},\n  keywords      = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n BUP-TR: Bayesian Underdetermined Projection Trust-Region Methods for Derivative-Free Optimization.\n \n \n \n \n\n\n \n Hu, W.; Xie, P.; Yuan, Y.; and Zhang, L.\n\n\n \n\n\n\n 2026.\n \n\n\n\n
\n\n\n\n \n \n \"BUP-TR:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{hu-xie-yuan-zhang-2026-bup-tr,\n  author        = {Wei Hu and Pengcheng Xie and Ya-xiang Yuan and Li Zhang},\n  title         = {{BUP-TR}: {Bayesian} Underdetermined Projection Trust-Region Methods for Derivative-Free Optimization},\n  year          = {2026},\n  eprint        = {2605.30841},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2605.30841},\n  keywords      = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Distributed Gradient-Regularized Newton Method: Scheduled Consensus and $O(ε^{-1})$ Global Iteration Complexity.\n \n \n \n \n\n\n \n Hu, W.; Xie, P.; Yuan, Y.; and Zhang, L.\n\n\n \n\n\n\n 2026.\n \n\n\n\n
\n\n\n\n \n \n \"DistributedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{hu-xie-yuan-zhang-2026-distributed-newton,\n  author        = {Wei Hu and Pengcheng Xie and Ya-xiang Yuan and Li Zhang},\n  title         = {Distributed Gradient-Regularized {Newton} Method: Scheduled Consensus and {$O(\\epsilon^{-1})$} Global Iteration Complexity},\n  year          = {2026},\n  eprint        = {2605.19396},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2605.19396},\n  keywords      = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Privacy-Preserving Black-Box Optimization (PBBO): Theory and the Model-Based Algorithm DFOp.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n 2026.\n \n\n\n\n
\n\n\n\n \n \n \"Privacy-PreservingPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@misc{xie-2026-pbbo,\n  author        = {Pengcheng Xie},\n  title         = {Privacy-Preserving Black-Box Optimization ({PBBO}): Theory and the Model-Based Algorithm {DFOp}},\n  year          = {2026},\n  eprint        = {2601.11570},\n  archivePrefix = {arXiv},\n  primaryClass  = {cs.CR},\n  url           = {https://arxiv.org/abs/2601.11570},\n  keywords      = {optimization, privacy}\n}\n\n
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\n  \n 2025\n \n \n (9)\n \n \n
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\n \n\n \n \n \n \n \n \n A New Derivative-Free Method Using an Improved Underdetermined Quadratic Interpolation Model.\n \n \n \n \n\n\n \n Xie, P.; and Yuan, Y.\n\n\n \n\n\n\n SIAM Journal on Optimization, 35(2): 1110–1133. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-yuan-2025-improved-underdetermined-model,\n  author  = {Pengcheng Xie and Ya-xiang Yuan},\n  title   = {A New Derivative-Free Method Using an Improved Underdetermined Quadratic Interpolation Model},\n  journal = {SIAM Journal on Optimization},\n  year    = {2025},\n  volume  = {35},\n  number  = {2},\n  pages   = {1110--1133},\n  doi     = {10.1137/23M1582023},\n  url     = {https://doi.org/10.1137/23M1582023},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Sufficient Conditions for Error Distance Reduction in the $\\ell_2$-Norm Trust Region Between Minimizers of Local Nonconvex Multivariate Quadratic Approximates.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n Journal of Computational and Applied Mathematics, 453: 116146. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"SufficientPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-2025-distance-reduction,\n  author  = {Pengcheng Xie},\n  title   = {Sufficient Conditions for Error Distance Reduction in the {$\\ell_2$}-Norm Trust Region Between Minimizers of Local Nonconvex Multivariate Quadratic Approximates},\n  journal = {Journal of Computational and Applied Mathematics},\n  year    = {2025},\n  volume  = {453},\n  pages   = {116146},\n  doi     = {10.1016/j.cam.2024.116146},\n  url     = {https://doi.org/10.1016/j.cam.2024.116146},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Derivative-Free Optimization with Transformed Objective Functions (DFOTO) and the Algorithm Based on the Least Frobenius Norm Updating Quadratic Model.\n \n \n \n \n\n\n \n Xie, P.; and Yuan, Y.\n\n\n \n\n\n\n Journal of the Operations Research Society of China, 13: 327–363. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"Derivative-FreePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-yuan-2025-dfoto,\n  author  = {Pengcheng Xie and Ya-xiang Yuan},\n  title   = {Derivative-Free Optimization with Transformed Objective Functions ({DFOTO}) and the Algorithm Based on the Least {Frobenius} Norm Updating Quadratic Model},\n  journal = {Journal of the Operations Research Society of China},\n  year    = {2025},\n  volume  = {13},\n  pages   = {327--363},\n  doi     = {10.1007/s40305-023-00532-x},\n  url     = {https://doi.org/10.1007/s40305-023-00532-x},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Spectral Levenberg–Marquardt-Deflation Method for Multiple Solutions of Semilinear Elliptic Systems.\n \n \n \n \n\n\n \n Li, L.; Zhou, Y.; Xie, P.; and Li, H.\n\n\n \n\n\n\n Journal of Computational and Applied Mathematics, 475: 116998. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{li-zhou-xie-li-2025-spectral-lm-deflation,\n  author  = {Lin Li and Yuheng Zhou and Pengcheng Xie and Huiyuan Li},\n  title   = {A Spectral {Levenberg--Marquardt}-Deflation Method for Multiple Solutions of Semilinear Elliptic Systems},\n  journal = {Journal of Computational and Applied Mathematics},\n  year    = {2025},\n  volume  = {475},\n  pages   = {116998},\n  doi     = {10.1016/j.cam.2025.116998},\n  url     = {https://doi.org/10.1016/j.cam.2025.116998},\n  keywords = {numerical PDE}\n}\n\n
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\n \n\n \n \n \n \n \n \n An Improved Adaptive Orthogonal Basis Deflation Method for Multiple Solutions with Applications to Nonlinear Elliptic Equations in Varying Domains.\n \n \n \n \n\n\n \n Ye, Y.; Li, L.; Xie, P.; and Yu, H.\n\n\n \n\n\n\n Journal of Computational Mathematics, 44(3): 794–818. 2025.\n \n\n\n\n
\n\n\n\n \n \n \"AnPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{ye-li-xie-yu-2025-adaptive-deflation,\n  author  = {Yangyi Ye and Lin Li and Pengcheng Xie and Haijun Yu},\n  title   = {An Improved Adaptive Orthogonal Basis Deflation Method for Multiple Solutions with Applications to Nonlinear Elliptic Equations in Varying Domains},\n  journal = {Journal of Computational Mathematics},\n  year    = {2025},\n  volume  = {44},\n  number  = {3},\n  pages   = {794--818},\n  doi     = {10.4208/jcm.2505-m2024-0276},\n  url     = {https://doi.org/10.4208/jcm.2505-m2024-0276},\n  keywords = {numerical PDE}\n}\n\n
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\n \n\n \n \n \n \n \n \n Optimization Approaches for Solving Inverse Problems Under Uncertainty.\n \n \n \n \n\n\n \n Dzahini, K. J.; Wild, S. M.; and Xie, P.\n\n\n \n\n\n\n Inverse Methods for Complex Systems under Uncertainty Workshop. 2025.\n Position paper, U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research\n\n\n\n
\n\n\n\n \n \n \"OptimizationPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{dzahini-wild-xie-2025-inverse-problems,\n  author  = {Kwassi J. Dzahini and Stefan M. Wild and Pengcheng Xie},\n  title   = {Optimization Approaches for Solving Inverse Problems Under Uncertainty},\n  journal = {Inverse Methods for Complex Systems under Uncertainty Workshop},\n  year    = {2025},\n  note    = {Position paper, U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research},\n  url     = {https://www.orau.gov/support_files/2025InverseMethods/WildS.pdf},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Novel Numerical Method Tailored for Unconstrained Optimization Problems.\n \n \n \n \n\n\n \n Li, L.; Xie, P.; and Zhang, L.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 7 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{li-xie-zhang-2025-novel-numerical-method,\n  author        = {Lin Li and Pengcheng Xie and Li Zhang},\n  title         = {A Novel Numerical Method Tailored for Unconstrained Optimization Problems},\n  year          = {2025},\n  eprint        = {2504.02832},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2504.02832},\n  keywords      = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Objective Value Change and Shape-Based Accelerated Optimization for Neural Network Approximation.\n \n \n \n \n\n\n \n Xie, P.; Zhou, Z.; and Zhou, Z.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"ObjectivePaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n \n \n\n\n\n
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@misc{xie-zhou-zhou-2025-shape-based-optimization,\n  author        = {Pengcheng Xie and Zihao Zhou and Zijian Zhou},\n  title         = {Objective Value Change and Shape-Based Accelerated Optimization for Neural Network Approximation},\n  year          = {2025},\n  eprint        = {2508.20290},\n  archivePrefix = {arXiv},\n  primaryClass  = {cs.LG},\n  url           = {https://arxiv.org/abs/2508.20290},\n  keywords      = {machine learning, optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy.\n \n \n \n \n\n\n \n He, Y.; and Xie, P.\n\n\n \n\n\n\n 2025.\n \n\n\n\n
\n\n\n\n \n \n \"Model-DrivenPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{he-xie-2025-model-driven-subspaces,\n  author        = {Yitong He and Pengcheng Xie},\n  title         = {Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy},\n  year          = {2025},\n  eprint        = {2509.08256},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2509.08256},\n  keywords      = {optimization}\n}\n\n
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\n  \n 2024\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n \n The Modeling and Optimization of a Multi-Dam System.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n Applied and Computational Mathematics, 13(5): 140–152. 2024.\n \n\n\n\n
\n\n\n\n \n \n \"ThePaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@article{xie-2024-multidam,\n  author  = {Pengcheng Xie},\n  title   = {The Modeling and Optimization of a Multi-Dam System},\n  journal = {Applied and Computational Mathematics},\n  year    = {2024},\n  volume  = {13},\n  number  = {5},\n  pages   = {140--152},\n  doi     = {10.11648/j.acm.20241305.13},\n  url     = {https://doi.org/10.11648/j.acm.20241305.13},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n On the Relationship Between $Λ$-Poisedness in Derivative-Free Optimization and Outliers in Local Outlier Factor.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
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@misc{xie-2024-lambda-poisedness-lof,\n  author        = {Pengcheng Xie},\n  title         = {On the Relationship Between {$\\Lambda$}-Poisedness in Derivative-Free Optimization and Outliers in Local Outlier Factor},\n  year          = {2024},\n  eprint        = {2407.17529},\n  archivePrefix = {arXiv},\n  primaryClass  = {math.OC},\n  url           = {https://arxiv.org/abs/2407.17529},\n  keywords      = {optimization, approximation}\n}\n\n
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\n \n\n \n \n \n \n \n Barycenter of the Weight-Coefficient Region of Least-Weighted $H^2$ Norm Updating Quadratic Models with Vanishing Trust-Region Radius.\n \n \n \n\n\n \n Xie, P.; and Wild, S. M.\n\n\n \n\n\n\n 2024.\n SIAM Northern and Central California Sectional Conference (NCC24), Early Career Travel Award\n\n\n\n
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@misc{xie-wild-2024-h2-barycenter,\n  author   = {Pengcheng Xie and Stefan M. Wild},\n  title    = {Barycenter of the Weight-Coefficient Region of Least-Weighted {$H^2$} Norm Updating Quadratic Models with Vanishing Trust-Region Radius},\n  year     = {2024},\n  note     = {SIAM Northern and Central California Sectional Conference (NCC24), Early Career Travel Award},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n A Novel Local Analysis of Objectives Approximated by Neural Networks: L-Change.\n \n \n \n\n\n \n Xie, P.; and others\n\n\n \n\n\n\n 2024.\n International Conference on Mathematical Theory of Deep Learning (MTDL)\n\n\n\n
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@misc{xie-etal-2024-l-change,\n  author   = {Pengcheng Xie and others},\n  title    = {A Novel Local Analysis of Objectives Approximated by Neural Networks: {L-Change}},\n  year     = {2024},\n  note     = {International Conference on Mathematical Theory of Deep Learning (MTDL)},\n  keywords = {machine learning, neural network}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Low-Computation-Cost Cubic-Regularized Quasi-Newton Method for Distributed Optimization: LC3RQN.\n \n \n \n \n\n\n \n Hu, W.; Xie, P.; Zhang, L.; and Yuan, Y.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
\n\n\n\n \n \n \"APaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 29 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n \n \n\n\n\n
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@misc{hu-xie-zhang-yuan-2024-lc3rqn,\n  author   = {Wei Hu and Pengcheng Xie and Li Zhang and Ya-xiang Yuan},\n  title    = {A Low-Computation-Cost Cubic-Regularized Quasi-{Newton} Method for Distributed Optimization: {LC3RQN}},\n  year     = {2024},\n  url      = {https://lsec.cc.ac.cn/~moa2024/Poster_List.pdf},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n An Efficient Derivative-Free Method for Finding Multiple Solutions.\n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n 2024.\n Manuscript\n\n\n\n
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@misc{xie-2024-multiple-solutions,\n  author   = {Pengcheng Xie},\n  title    = {An Efficient Derivative-Free Method for Finding Multiple Solutions},\n  year     = {2024},\n  note     = {Manuscript},\n  keywords = {numerical PDE}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Note on the Invariant Distribution of a Stochastic Dynamical System.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n 2024.\n \n\n\n\n
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@misc{xie-2024-invariant-distribution,\n  author   = {Pengcheng Xie},\n  title    = {A Note on the Invariant Distribution of a Stochastic Dynamical System},\n  year     = {2024},\n  doi      = {10.12074/202304.01048},\n  url      = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4910398},\n  keywords = {control}\n}\n\n
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\n  \n 2023\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n \n A Derivative-Free Optimization Algorithm Combining Line-Search and Trust-Region Techniques.\n \n \n \n \n\n\n \n Xie, P.; and Yuan, Y.\n\n\n \n\n\n\n Chinese Annals of Mathematics, Series B, 44(5): 693–708. 2023.\n \n\n\n\n
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@article{xie-yuan-2023-line-search-trust-region,\n  author  = {Pengcheng Xie and Ya-xiang Yuan},\n  title   = {A Derivative-Free Optimization Algorithm Combining Line-Search and Trust-Region Techniques},\n  journal = {Chinese Annals of Mathematics, Series B},\n  year    = {2023},\n  volume  = {44},\n  number  = {5},\n  pages   = {693--708},\n  doi     = {10.1007/s11401-023-0040-y},\n  url     = {https://doi.org/10.1007/s11401-023-0040-y},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n A Derivative-Free Trust-Region Method for Optimization on the Ellipsoid.\n \n \n \n \n\n\n \n Xie, P.\n\n\n \n\n\n\n Journal of Physics: Conference Series, 2620: 012007. 2023.\n Presented at the 2023 International Conference on Advances in Computer Science and Engineering Technology\n\n\n\n
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@article{xie-2023-ellipsoid,\n  author  = {Pengcheng Xie},\n  title   = {A Derivative-Free Trust-Region Method for Optimization on the Ellipsoid},\n  journal = {Journal of Physics: Conference Series},\n  year    = {2023},\n  volume  = {2620},\n  pages   = {012007},\n  doi     = {10.1088/1742-6596/2620/1/012007},\n  url     = {https://doi.org/10.1088/1742-6596/2620/1/012007},\n  note    = {Presented at the 2023 International Conference on Advances in Computer Science and Engineering Technology},\n  keywords = {optimization}\n}\n\n
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\n \n\n \n \n \n \n \n \n Simulation of Interaction of Folded Waveguide Space Traveling Wave Tubes with Derivative-Free Mixed-Integer-Based NEWUOA Algorithm.\n \n \n \n \n\n\n \n Li, S.; Xie, P.; Zhou, Z.; and others\n\n\n \n\n\n\n In 2021 7th International Conference on Computer and Communications (ICCC), pages 1215–1219, 2021. \n \n\n\n\n
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@inproceedings{li-xie-zhou-etal-2021-newuoa,\n  author    = {Shuoran Li and Pengcheng Xie and Zihao Zhou and others},\n  title     = {Simulation of Interaction of Folded Waveguide Space Traveling Wave Tubes with Derivative-Free Mixed-Integer-Based {NEWUOA} Algorithm},\n  booktitle = {2021 7th International Conference on Computer and Communications (ICCC)},\n  year      = {2021},\n  pages     = {1215--1219},\n  doi       = {10.1109/ICCC54389.2021.9674410},\n  url       = {https://doi.org/10.1109/ICCC54389.2021.9674410},\n  keywords  = {optimization}\n}\n
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\n  \n 2019\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n \n Parametric Resonant Control of Macroscopic Behaviors of Multiple Oscillators.\n \n \n \n \n\n\n \n Xie, P.; and Tao, M.\n\n\n \n\n\n\n In 2019 American Control Conference (ACC), pages 1898–1905, 2019. \n \n\n\n\n
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@inproceedings{xie-tao-2019-acc,\n  author    = {Pengcheng Xie and Molei Tao},\n  title     = {Parametric Resonant Control of Macroscopic Behaviors of Multiple Oscillators},\n  booktitle = {2019 American Control Conference (ACC)},\n  year      = {2019},\n  pages     = {1898--1905},\n  doi       = {10.23919/ACC.2019.8814709},\n  url       = {https://doi.org/10.23919/ACC.2019.8814709},\n  keywords  = {control}\n}\n\n
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