Zhiwei Steven Wu

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Aaron RothProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Michael KearnsProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Seth NeelAsst Professor, Harvard UniversityVerified email at hbs.edu
Katrina LigettHebrew UniversityVerified email at mail.huji.ac.il
Vasilis SyrgkanisAssistant Professor, Stanford UniversityVerified email at stanford.edu
Bo WaggonerUniversity of Colorado, BoulderVerified email at colorado.edu
Jonathan UllmanAssociate Professor of Computer Science, Northeastern UniversityVerified email at ccs.neu.edu
Brett Beaulieu-JonesUniversity of ChicagoVerified email at uchicago.edu
Rachel CummingsColumbia UniversityVerified email at columbia.edu
Yishay MansourTel Aviv UniversityVerified email at tauex.tau.ac.il
Justin HsuCornell UniversityVerified email at justinhsu.net
Juba ZianiGeorgia Institute of Technology (IsyE)Verified email at isye.gatech.edu
Jamie MorgensternUniversity of WashingtonVerified email at cs.washington.edu
Ryan RogersLinkedInVerified email at linkedin.com
Casey S. GreeneBiomedical Informatics; Center for Health AI; University of Colorado Anschutz MedicalVerified email at cuanschutz.edu
Zhiyi HuangThe University of Hong KongVerified email at cs.hku.hk
Manish RaghavanMITVerified email at mit.edu
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityVerified email at microsoft.com
Shahin JabbariHarvard UniversityVerified email at seas.harvard.edu
Grigory YaroslavtsevAssistant Professor, George Mason UniversityVerified email at grigory.us

Zhiwei Steven Wu

Other namesSteven Wu

Carnegie Mellon University

Verified email at andrew.cmu.edu - Homepage

Machine Learning Differential Privacy Algorithmic Fairness Algorithmic Game Theory


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Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness M Kearns, S Neel, A Roth, ZS Wu The 35th International Conference on Machine Learning (ICML'18), 2017	545	2017
Privacy-preserving generative deep neural networks support clinical data sharing BK Beaulieu-Jones, ZS Wu, C Williams, R Lee, SP Bhavnani, JB Byrd, ... Circulation: Cardiovascular Quality and Outcomes, 2019	289	2019
Fair regression: Quantitative definitions and reduction-based algorithms A Agarwal, M Dudík, ZS Wu International Conference on Machine Learning, 120-129, 2019	148	2019
An empirical study of rich subgroup fairness for machine learning M Kearns, S Neel, A Roth, ZS Wu The Second Annual ACM Conference on Fairness, Accountability, and …, 2018	136	2018
Strategic classification from revealed preferences J Dong, A Roth, Z Schutzman, B Waggoner, ZS Wu Proceedings of the 2018 ACM Conference on Economics and Computation, 55-70, 2018	114	2018
Bayesian exploration: Incentivizing exploration in bayesian games Y Mansour, A Slivkins, V Syrgkanis, ZS Wu The 17th ACM Conference on Economics and Computation (EC 2016), 2016	85*	2016
Orthogonal random forest for causal inference M Oprescu, V Syrgkanis, ZS Wu International Conference on Machine Learning, 4932-4941, 2019	83*	2019
Understanding gradient clipping in private SGD: A geometric perspective X Chen, SZ Wu, M Hong Advances in Neural Information Processing Systems 33, 13773-13782, 2020	81	2020
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem S Kannan, J Morgenstern, A Roth, B Waggoner, ZS Wu The Thirty-second Conference on Neural Information Processing Systems (NIPS …, 2018	81	2018
Accuracy first: Selecting a differential privacy level for accuracy constrained erm K Ligett, S Neel, A Roth, B Waggoner, SZ Wu Advances in Neural Information Processing Systems 30, 2017	78	2017
Dual Query: Practical Private Query Release for High Dimensional Data M Gaboardi, EJG Arias, J Hsu, A Roth, ZS Wu The 31st International Conference on Machine Learning (ICML 2014), 2014	77	2014
Private matchings and allocations J Hsu, Z Huang, A Roth, T Roughgarden, ZS Wu The 46th ACM Symposium on Theory of Computing (STOC 2014), 2014	77	2014
An algorithmic framework for fairness elicitation C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu arXiv preprint arXiv:1905.10660, 2019	69*	2019
Meritocratic fairness for cross-population selection M Kearns, A Roth, ZS Wu International Conference on Machine Learning, 1828-1836, 2017	59	2017
Adaptive learning with robust generalization guarantees R Cummings, K Ligett, K Nissim, A Roth, ZS Wu Conference on Learning Theory, 772-814, 2016	55	2016
Private hypothesis selection M Bun, G Kamath, T Steinke, SZ Wu Advances in Neural Information Processing Systems 32, 2019	52	2019
Bypassing the ambient dimension: Private sgd with gradient subspace identification Y Zhou, ZS Wu, A Banerjee arXiv preprint arXiv:2007.03813, 2020	50	2020
The Externalities of Exploration and How Data Diversity Helps Exploitation M Raghavan, A Slivkins, JW Vaughan, ZS Wu The 31st Annual Conference on Learning Theory (COLT'18), 2018	50	2018
Private algorithms for the protected in social network search M Kearns, A Roth, ZS Wu, G Yaroslavtsev Proceedings of the National Academy of Sciences 113 (4), 913-918, 2016	50*	2016
Watch and learn: Optimizing from revealed preferences feedback A Roth, J Ullman, ZS Wu Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing …, 2015	49	2015

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