Wu, Steven Z.

25 publications

NeurIPS 2023 Adaptive Principal Component Regression with Applications to Panel Data Anish Agarwal, Keegan Harris, Justin Whitehouse, Steven Z. Wu

NeurIPS 2023 Adaptive Privacy Composition for Accuracy-First Mechanisms Ryan M Rogers, Gennady Samorodnitsk, Steven Z. Wu, Aaditya Ramdas

NeurIPS 2023 Learning Shared Safety Constraints from Multi-Task Demonstrations Konwoo Kim, Gokul Swamy, Zuxin Liu, Ding Zhao, Sanjiban Choudhury, Steven Z. Wu

NeurIPS 2023 Meta-Learning Adversarial Bandit Algorithms Misha Khodak, Ilya Osadchiy, Keegan Harris, Maria-Florina F Balcan, Kfir Y. Levy, Ron Meir, Steven Z. Wu

NeurIPS 2023 On the Sublinear Regret of GP-UCB Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu

NeurIPS 2023 Scalable Membership Inference Attacks via Quantile Regression Martin Bertran, Shuai Tang, Aaron Roth, Michael J. Kearns, Jamie H Morgenstern, Steven Z. Wu

NeurIPS 2023 Strategic Apple Tasting Keegan Harris, Chara Podimata, Steven Z. Wu

NeurIPS 2022 Bayesian Persuasion for Algorithmic Recourse Keegan Harris, Valerie Chen, Joon Kim, Ameet Talwalkar, Hoda Heidari, Steven Z. Wu

NeurIPS 2022 Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse, Aaditya Ramdas, Steven Z. Wu, Ryan M Rogers

NeurIPS 2022 Incentivizing Combinatorial Bandit Exploration Xinyan Hu, Dung Ngo, Aleksandrs Slivkins, Steven Z. Wu

NeurIPS 2022 Minimax Optimal Online Imitation Learning via Replay Estimation Gokul Swamy, Nived Rajaraman, Matt Peng, Sanjiban Choudhury, J. A. Bagnell, Steven Z. Wu, Jiantao Jiao, Kannan Ramchandran

NeurIPS 2022 On Privacy and Personalization in Cross-Silo Federated Learning Ken Liu, Shengyuan Hu, Steven Z. Wu, Virginia Smith

NeurIPS 2022 Private Synthetic Data for Multitask Learning and Marginal Queries Giuseppe Vietri, Cedric Archambeau, Sergul Aydore, William Brown, Michael J. Kearns, Aaron Roth, Ankit Siva, Shuai Tang, Steven Z. Wu

NeurIPS 2022 Sequence Model Imitation Learning with Unobserved Contexts Gokul Swamy, Sanjiban Choudhury, J. A. Bagnell, Steven Z. Wu

NeurIPS 2021 Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods Terrance Liu, Giuseppe Vietri, Steven Z. Wu

NeurIPS 2021 Stateful Strategic Regression Keegan Harris, Hoda Heidari, Steven Z. Wu

NeurIPS 2020 Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms Xiangyi Chen, Tiancong Chen, Haoran Sun, Steven Z. Wu, Mingyi Hong

NeurIPS 2020 Metric-Free Individual Fairness in Online Learning Yahav Bechavod, Christopher Jung, Steven Z. Wu

NeurIPS 2020 Understanding Gradient Clipping in Private SGD: A Geometric Perspective Xiangyi Chen, Steven Z. Wu, Mingyi Hong

NeurIPS 2019 Equal Opportunity in Online Classification with Partial Feedback Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Steven Z. Wu

NeurIPS 2019 Locally Private Gaussian Estimation Matthew Joseph, Janardhan Kulkarni, Jieming Mao, Steven Z. Wu

NeurIPS 2019 Private Hypothesis Selection Mark Bun, Gautam Kamath, Thomas Steinke, Steven Z. Wu

NeurIPS 2019 Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Steven Z. Wu

NeurIPS 2017 Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM Katrina Ligett, Seth Neel, Aaron Roth, Bo Waggoner, Steven Z. Wu

NeurIPS 2016 Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs Shahin Jabbari, Ryan M Rogers, Aaron Roth, Steven Z. Wu