BibBase curry, m

2024 (1)

Automated Design of Affine Maximizer Mechanisms In Dynamic Settings. Curry, M. J.; Thoma, V.; Chakrabarti, D.; McAleer, S. M.; Kroer, C.; Sandholm, T.; He, N.; and Seuken, S. In AAAI Conference on Artificial Intelligence, 2024.
link bibtex

@inproceedings{curry2023automated,
  title={Automated Design of Affine Maximizer Mechanisms In Dynamic Settings},
  author={Curry, Michael J. and Thoma, Vinzenz and Chakrabarti, Darshan and McAleer, Stephen Marcus and Kroer, Christian and Sandholm, Tuomas and He, Niao and Seuken, Sven},
  year={2024},
  booktitle=AAAI
}

2023 (2)

Differentiable Economics for Randomized Affine Maximizer Auctions. Curry, M. J.; Sandholm, T.; and Dickerson, J. P. In International Joint Conference on Artificial Intelligence (IJCAI), 2023.
link bibtex

@inproceedings{curry2023differentiable,
  author    = {Michael J. Curry and
               Tuomas Sandholm and
               John P. Dickerson},
  title     = {Differentiable Economics for Randomized Affine Maximizer Auctions},
  year = {2023},
  booktitle = IJCAI
}

Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning: Extended Abstract. Curry, M.; Trott, A.; Phade, S.; Bai, Y.; and Zheng, S. In International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2023.
link bibtex

@inproceedings{DBLP:journals/corr/abs-2201-01163,
  author    = {Michael Curry and
               Alexander Trott and
               Soham Phade and
               Yu Bai and
               Stephan Zheng},
  title     = {Learning Solutions in Large Economic Networks using Deep Multi-Agent Reinforcement Learning: Extended Abstract},
  year      = {2023},
  booktitle=AAMAS
}

2022 (2)

Certified Neural Network Watermarks with Randomized Smoothing. Bansal, A.; Chiang, P.; Curry, M. J; Jain, R.; Wigington, C.; Manjunatha, V.; Dickerson, J. P; and Goldstein, T. In International Conference on Machine Learning (ICML), 2022.
link bibtex

@InProceedings{pmlr-v162-bansal22a,
  title =      {Certified Neural Network Watermarks with Randomized Smoothing},
  author =       {Bansal, Arpit and Chiang, Ping-Yeh and Curry, Michael J and Jain, Rajiv and Wigington, Curtis and Manjunatha, Varun and Dickerson, John P and Goldstein, Tom},
  booktitle = ICML,
  year =      {2022},
}

Learning Revenue-Maximizing Auctions With Differentiable Matching. Curry, M. J.; Lyi, U.; Goldstein, T.; and Dickerson, J. In Artificial Intelligence and Statistics, 2022.
link bibtex

@inproceedings{DBLP:journals/corr/abs-2106-07877,
  author    = {Michael J. Curry and
               Uro Lyi and
               Tom Goldstein and
               John Dickerson},
  title     = {Learning Revenue-Maximizing Auctions With Differentiable Matching},
  booktitle=aistats,
  year      = {2022},
}

2021 (4)

Who Can be Matched via Kidney Exchange?. McElfresh, D.; Curry, M; Booker, S.; Stewart, D; Stuart, M; Leishman, R; Sandholm, T; and Dickerson, J In American Journal of Transplantation, 2021.
link bibtex

@inproceedings{mcelfresh2021can,
  title={Who Can be Matched via Kidney Exchange?},
  author={McElfresh, DC and Curry, M and Booker, SE and Stewart, D and Stuart, M and Leishman, R and Sandholm, T and Dickerson, J},
  booktitle={American Journal of Transplantation},
  year={2021},
}

Globally Certifiable Deep Auctions. Chiang, P.; Curry, M. J.; Goldstein, T.; and Dickerson, J. In submission, available on request. 2021.
link bibtex

@article{chiang2020global,
   author={Ping-yeh Chiang and Michael J. Curry and Tom Goldstein and John Dickerson},
   year={2021},
   title={Globally Certifiable Deep Auctions},
   journal=subrequest
}

PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning. Peri, N.; Curry, M. J.; Dooley, S.; and Dickerson, J. P. In Neural Information Processing Systems (NeurIPS), 2021.
link bibtex

@inproceedings{DBLP:journals/corr/abs-2106-03215,
  author    = {Neehar Peri and
               Michael J. Curry and
               Samuel Dooley and
               John P. Dickerson},
  title     = {PreferenceNet: Encoding Human Preferences in Auction Design with Deep
               Learning},
  year      = {2021},
  booktitle=nips,
}

Scalable Equilibrium Computation in Multi-Player Influence Games on Networks. Christia, F.; Curry, M. J.; Daskalakis, C.; Demaine, E.; Dickerson, J.; Hajiaghayi, M.; Hesterberg, A.; Knittel, M.; and Milliff, A. In AAAI Conference on Artificial Intelligence, 2021.
link bibtex

@inproceedings{christia2020influence,
    title={Scalable Equilibrium Computation in Multi-Player Influence Games on Networks},
    author={Fotini Christia and Michael J. Curry and Constantinos Daskalakis and Erik Demaine and John Dickerson and MohammadTaghi Hajiaghayi and Adam Hesterberg and Marina Knittel and Aidan Milliff},
    year={2021},
    booktitle=aaai
}

2020 (6)

Certified Watermarks for Neural Networks. Bansal, A.; Chiang, P.; Curry, M.; Manjunatha, V.; Jain, R.; and Goldstein, T. In submission, available on request. 2020.
link bibtex

@article{chiang2020watermarks,
   title={Certified Watermarks for Neural Networks},
   author={Arpit Bansal and Ping-Yeh Chiang and Michael Curry and Varun Manjunatha and Rajiv Jain and Tom Goldstein},
   year={2020},
   journal=subrequest
}

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. Kuo, K.; Ostuni, A.; Horishny, E.; Curry, M. J.; Dooley, S.; Chiang, P.; Goldstein, T.; and Dickerson, J. P. CoRR, abs/2010.06398. 2020.
link bibtex

@article{DBLP:journals/corr/abs-2010-06398,
  author    = {Kevin Kuo and
               Anthony Ostuni and
               Elizabeth Horishny and
               Michael J. Curry and
               Samuel Dooley and
               Ping{-}Yeh Chiang and
               Tom Goldstein and
               John P. Dickerson},
  title     = {ProportionNet: Balancing Fairness and Revenue for Auction Design with
               Deep Learning},
  journal   = {CoRR},
  volume    = {abs/2010.06398},
  year      = {2020},
  archivePrefix = {arXiv},
  eprint    = {2010.06398},
  timestamp = {Tue, 20 Oct 2020 15:08:10 +0200},
addendum=workingpaper
}

Detection as Regression: Certified Object Detection by Median Smoothing. Chiang, P.; Curry, M. J.; Abdelkader, A.; Kumar, A.; Dickerson, J.; and Goldstein, T. In Neural Information Processing Systems (NeurIPS), 2020.
link bibtex

@inproceedings{chiang2020detection,
    title={Detection as Regression: Certified Object Detection by Median Smoothing},
    author={Ping-Yeh Chiang and Michael J. Curry and Ahmed Abdelkader and Aounon Kumar and John Dickerson and Tom Goldstein},
    year={2020},
    booktitle=nips
}

Improving Policy-Constrained Kidney Exchange via Pre-Screening. McElfresh, D.; Curry, M. J.; Sandholm, T.; and Dickerson, J. In Neural Information Processing Systems (NeurIPS), 2020.
link bibtex

@inproceedings{mcelfresh2020prescreen,
    title={Improving Policy-Constrained Kidney Exchange via Pre-Screening},
    author={Duncan McElfresh and Michael J. Curry and Tuomas Sandholm and John Dickerson},
    year={2020},
    booktitle=nips
}

Certifying Strategyproof Auction Networks. Curry, M. J.; Chiang, P.; Goldstein, T.; and Dickerson, J. In Neural Information Processing Systems (NeurIPS), 2020.
link bibtex

@inproceedings{curry2020certifying,
  title={Certifying Strategyproof Auction Networks},
  author={Curry, Michael J. and Chiang, Ping-Yeh and Goldstein, Tom and Dickerson, John},
  booktitle=nips,
  year={2020},
}

Headless Horseman: Adversarial Attacks on Transfer Learning Models. Abdelkader, A.; Curry, M. J.; Fowl, L.; Goldstein, T.; Schwarzschild, A.; Shu, M.; Studer, C.; and Zhu, C. In International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 3087–3091, 2020.
link bibtex

@inproceedings{AbdelkaderCFGSSSZ20headless,
  title={Headless Horseman: Adversarial Attacks on Transfer Learning Models},
  author={Abdelkader, Ahmed and Curry, Michael J. and Fowl, Liam and Goldstein, Tom and Schwarzschild, Avi and Shu, Manli and Studer, Christoph and Zhu, Chen},
  booktitle=icassp,
  pages={3087--3091},
  year={2020},
}

2019 (2)

Reinforcement Learning for Dynamic Set Packing. Curry, M. J.; McElFresh, D.; You, X.; Moy, C.; Huang, F.; Goldstein, T.; and Dickerson, J. P. In Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2019.
link bibtex

@inproceedings{CurryWineDynamic19,
 author     = {Michael J. Curry and Duncan McElFresh and Xuchen You and Cameron Moy and Furong Huang and Tom Goldstein and John P. Dickerson},
 title      = {Reinforcement Learning for Dynamic Set Packing},
 booktitle = "Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM)",
 year       = {2019}
}

Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare. Curry, M. J.; Dickerson, J. P.; Sankararaman, K. A.; Srinivasan, A.; Wan, Y.; and Xu, P. In Conference on Web and Internet Economics (WINE), 2019.
link bibtex

@inproceedings{CurryDSSW19MixMatch,
  author    = {Michael J. Curry and
               John P. Dickerson and
               Karthik Abinav Sankararaman and
               Aravind Srinivasan and
               Yuhao Wan and
               Pan Xu},
  title     = {Mix and Match: Markov Chains and Mixing Times for Matching in Rideshare},
  booktitle = wine,
  year      = {2019},
}

2013 (1)

A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies. Walker, L.; Curry, M. J.; Nayak, A.; Lange, N.; Pierpaoli, C.; and Group, B. D. C. Human brain mapping, 34(10): 2439–2454. 2013.
link bibtex

@article{walker2013framework,
  title={A framework for the analysis of phantom data in multicenter diffusion tensor imaging studies},
  author={Walker, Lindsay and Curry, Michael J. and Nayak, Amritha and Lange, Nicholas and Pierpaoli, Carlo and Brain Development Cooperative Group},
  journal={Human brain mapping},
  volume={34},
  number={10},
  pages={2439--2454},
  year={2013},
  publisher={Wiley Online Library}
}

2012 (2)

Diffusion Tensor Uncertainty: Visualization and Similarity Metrics. Irfanoglu, M. O.; Curry, M. J.; Özarslan, E.; Koay, C. G.; Pajevic, S.; and Basser, P. J In Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM), 2012.
link bibtex

@inproceedings{irfanogludiffusion,
  title={Diffusion Tensor Uncertainty: Visualization and Similarity Metrics},
  author={Irfanoglu, Mustafa Okan and Curry, Michael J. and {\"O}zarslan, Evren and Koay, Cheng Guan and Pajevic, Sinisa and Basser, Peter J},
  booktitle = ismrm,
  year      = {2012},
}

Impact of the Analysis of Phantoms on Data Quality for the DTI Component of the NIH MRI Study of Normal Brain Development. Walker, L.; Curry, M. J.; Amritha, N.; Lange, N.; Pierpaoli, C.; and Group, T. B. D. C. In Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM), 2012.
link bibtex

@inproceedings{walker2012framework,
title={Impact of the Analysis of Phantoms on Data Quality for the DTI Component of the NIH MRI Study of Normal Brain Development},
booktitle=ismrm,
author={Walker, Lindsay and Curry, Michael J. and Nayak Amritha and Lange, Nicholas and Pierpaoli, Carlo and The Brain Development Cooperative Group},
year={2012},
}

2011 (1)

Bias in Diffusion Tensor-Derived Quantities Depend on The Number of DWIs Composing The DT-MRI Dataset. Tannazi, F.; Walker, L.; Curry, M. J.; and Pierpaoli, C. In Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM), 2011.
link bibtex

@inproceedings{tannazi1939bias,
  title={Bias in Diffusion Tensor-Derived Quantities Depend on The Number of DWIs Composing The DT-MRI Dataset},
  author={Tannazi, Firouzeh and Walker, Lindsay and Curry, Michael J. and Pierpaoli, Carlo},
  booktitle=ismrm,
  year={2011},
}