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Zhiwei Steven Wu
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Cited by
Year
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
8062017
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
4132019
Fair regression: Quantitative definitions and reduction-based algorithms
A Agarwal, M Dudík, ZS Wu
International Conference on Machine Learning, 120-129, 2019
2522019
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
2082018
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
1792018
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
1752020
The disagreement problem in explainable machine learning: A practitioner's perspective
S Krishna, T Han, A Gu, J Pombra, S Jabbari, S Wu, H Lakkaraju
arXiv preprint arXiv:2202.01602, 2022
1372022
Orthogonal random forest for causal inference
M Oprescu, V Syrgkanis, ZS Wu
International Conference on Machine Learning, 4932-4941, 2019
122*2019
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
109*2016
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
1062018
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
1012017
Bypassing the ambient dimension: Private sgd with gradient subspace identification
Y Zhou, ZS Wu, A Banerjee
arXiv preprint arXiv:2007.03813, 2020
1002020
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
992014
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
932014
An algorithmic framework for fairness elicitation
C Jung, M Kearns, S Neel, A Roth, L Stapleton, ZS Wu
arXiv preprint arXiv:1905.10660, 2019
89*2019
Private hypothesis selection
M Bun, G Kamath, T Steinke, SZ Wu
Advances in Neural Information Processing Systems 32, 2019
842019
Improving human-AI partnerships in child welfare: understanding worker practices, challenges, and desires for algorithmic decision support
A Kawakami, V Sivaraman, HF Cheng, L Stapleton, Y Cheng, D Qing, ...
Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022
732022
New oracle-efficient algorithms for private synthetic data release
G Vietri, G Tian, M Bun, T Steinke, S Wu
International Conference on Machine Learning, 9765-9774, 2020
732020
Distributed training with heterogeneous data: Bridging median-and mean-based algorithms
X Chen, T Chen, H Sun, SZ Wu, M Hong
Advances in Neural Information Processing Systems 33, 21616-21626, 2020
662020
Meritocratic fairness for cross-population selection
M Kearns, A Roth, ZS Wu
International conference on machine learning, 1828-1836, 2017
662017
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Articles 1–20