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Of Moments and Matching: Trade-offs and Treatments in Imitation Learning


Mar 04, 2021
Gokul Swamy, Sanjiban Choudhury, Zhiwei Steven Wu, J. Andrew Bagnell


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Information Discrepancy in Strategic Learning


Mar 03, 2021
Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, Juba Ziani


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Towards the Unification and Robustness of Perturbation and Gradient Based Explanations


Feb 21, 2021
Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Zhiwei Steven Wu, Himabindu Lakkaraju


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Leveraging Public Data for Practical Private Query Release


Feb 17, 2021
Terrance Liu, Giuseppe Vietri, Thomas Steinke, Jonathan Ullman, Zhiwei Steven Wu


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Private Reinforcement Learning with PAC and Regret Guarantees


Sep 18, 2020
Giuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu


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Bandit Data-driven Optimization: AI for Social Good and Beyond


Aug 26, 2020
Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang


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Private Post-GAN Boosting


Jul 23, 2020
Marcel Neunhoeffer, Zhiwei Steven Wu, Cynthia Dwork


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Competing Bandits: The Perils of Exploration Under Competition


Jul 20, 2020
Guy Aridor, Yishay Mansour, Aleksandrs Slivkins, Zhiwei Steven Wu

* merged and extended version of arXiv:1702.08533 and arXiv:1902.05590 

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New Oracle-Efficient Algorithms for Private Synthetic Data Release


Jul 10, 2020
Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Zhiwei Steven Wu


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Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification


Jul 07, 2020
Yingxue Zhou, Zhiwei Steven Wu, Arindam Banerjee


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Understanding Gradient Clipping in Private SGD: A Geometric Perspective


Jun 27, 2020
Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong


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Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds


Jun 24, 2020
Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee


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Greedy Algorithm almost Dominates in Smoothed Contextual Bandits


May 19, 2020
Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu

* Results in this paper, without any proofs, have been announced in an extended abstract (Raghavan et al., 2018a), and fleshed out in the technical report (Raghavan et al., 2018b [arXiv:1806.00543]). This manuscript covers a subset of results from Raghavan et al. (2018a,b), focusing on the greedy algorithm, and is streamlined accordingly 

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Private Query Release Assisted by Public Data


Apr 23, 2020
Raef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan Ullman, Zhiwei Steven Wu


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Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis


Feb 26, 2020
Vidyashankar Sivakumar, Zhiwei Steven Wu, Arindam Banerjee


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Privately Learning Markov Random Fields


Feb 21, 2020
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Zhiwei Steven Wu


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Locally Private Hypothesis Selection


Feb 21, 2020
Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang


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Metric-Free Individual Fairness in Online Learning


Feb 17, 2020
Yahav Bechavod, Christopher Jung, Zhiwei Steven Wu


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Causal Feature Discovery through Strategic Modification


Feb 17, 2020
Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani


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Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization


Feb 13, 2020
Vikas K. Garg, Adam Kalai, Katrina Ligett, Zhiwei Steven Wu


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Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond


Oct 11, 2019
Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Zhiwei Steven Wu


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Differentially Private Objective Perturbation: Beyond Smoothness and Convexity


Sep 03, 2019
Seth Neel, Aaron Roth, Giuseppe Vietri, Zhiwei Steven Wu


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Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms


Jun 06, 2019
Xiangyi Chen, Tiancong Chen, Haoran Sun, Zhiwei Steven Wu, Mingyi Hong


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Private Hypothesis Selection


May 30, 2019
Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu


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Fair Regression: Quantitative Definitions and Reduction-based Algorithms


May 30, 2019
Alekh Agarwal, Miroslav Dudík, Zhiwei Steven Wu


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Eliciting and Enforcing Subjective Individual Fairness


May 25, 2019
Christopher Jung, Michael Kearns, Seth Neel, Aaron Roth, Logan Stapleton, Zhiwei Steven Wu


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Bayesian Exploration with Heterogeneous Agents


Feb 19, 2019
Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, Zhiwei Steven Wu


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Competing Bandits: The Perils of Exploration under Competition


Feb 14, 2019
Guy Aridor, Kevin Liu, Aleksandrs Slivkins, Zhiwei Steven Wu


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Equal Opportunity in Online Classification with Partial Feedback


Feb 06, 2019
Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu

* 28 pages 

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