More from the Same Authors

• 2021 Spotlight: Bayesian decision-making under misspecified priors with applications to meta-learning »
  Max Simchowitz · Christopher Tosh · Akshay Krishnamurthy · Daniel Hsu · Thodoris Lykouris · Miro Dudik · Robert Schapire
• 2021 : What Would the Expert do()?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods »
  Terrance Liu · Giuseppe Vietri · Steven Wu
• 2021 : What Would the Expert do()?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : What Would the Expert $do(\cdot)$?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : Bayesian Persuasion for Algorithmic Recourse »
  Keegan Harris · Valerie Chen · Joon Sik Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu
• 2021 : What Would the Expert $do(\cdot)$?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : Information Discrepancy in Strategic Learning »
  Yahav Bechavod · Chara Podimata · Steven Wu · Juba Ziani
• 2021 : Gaming Helps! Learning from Strategic Interactions in Natural Dynamics »
  Yahav Bechavod · Katrina Ligett · Steven Wu · Juba Ziani
• 2021 : Bayesian Persuasion for Algorithmic Recourse »
  Keegan Harris · Valerie Chen · Joon Kim · Ameet S Talwalkar · Hoda Heidari · Steven Wu
• 2021 : What Would the Expert $do(\cdot)$?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : What Would the Expert $do(\cdot)$?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : What Would the Expert $do(\cdot)$?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 : Information Discrepancy in Strategic Learning »
  Yahav Bechavod · Chara Podimata · Steven Wu · Juba Ziani
• 2021 : Gaming Helps! Learning from Strategic Interactions in Natural Dynamics »
  Yahav Bechavod · Katrina Ligett · Steven Wu · Juba Ziani
• 2021 : Bayesian Persuasion for Algorithmic Recourse »
  Keegan Harris · Valerie Chen · Joon Kim · Ameet S Talwalkar · Hoda Heidari · Steven Wu
• 2022 : Strategy-Aware Contextual Bandits »
  Keegan Harris · Chara Podimata · Steven Wu
• 2022 : Choosing Public Datasets for Private Machine Learning via Gradient Subspace Distance »
  Xin Gu · Gautam Kamath · Steven Wu
• 2022 : Strategy-Aware Contextual Bandits »
  Keegan Harris · Chara Podimata · Steven Wu
• 2022 : Strategy-Aware Contextual Bandits »
  Keegan Harris · Chara Podimata · Steven Wu
• 2022 : Differentially Private Gradient Boosting on Linear Learners for Tabular Data »
  Saeyoung Rho · Shuai Tang · Sergul Aydore · Michael Kearns · Aaron Roth · Yu-Xiang Wang · Steven Wu · Cedric Archambeau
• 2022 : Counterfactual Decision Support Under Treatment-Conditional Outcome Measurement Error »
  Luke Guerdan · Amanda Coston · Kenneth Holstein · Steven Wu
• 2023 Poster: Scalable Membership Inference Attacks via Quantile Regression »
  Martin Bertran · Shuai Tang · Aaron Roth · Michael Kearns · Jamie Morgenstern · Steven Wu
• 2023 Poster: Meta-Learning Adversarial Bandit Algorithms »
  Misha Khodak · Ilya Osadchiy · Keegan Harris · Maria-Florina Balcan · Kfir Y. Levy · Ron Meir · Steven Wu
• 2023 Poster: A Unified Model and Dimension for Interactive Estimation »
  Nataly Brukhim · Miro Dudik · Aldo Pacchiano · Robert Schapire
• 2023 Poster: Strategic Apple Tasting »
  Keegan Harris · Chara Podimata · Steven Wu
• 2023 Poster: Adaptive Privacy Composition for Accuracy-first Mechanisms »
  Ryan Rogers · Gennady Samorodnitsk · Steven Wu · Aaditya Ramdas
• 2023 Poster: Adaptive Principal Component Regression with Applications to Panel Data »
  Anish Agarwal · Keegan Harris · Justin Whitehouse · Steven Wu
• 2023 Poster: Improved Self-Normalized Concentration in Hilbert Spaces: Sublinear Regret for GP-UCB »
  Justin Whitehouse · Aaditya Ramdas · Steven Wu
• 2023 Poster: Learning Shared Safety Constraints from Multi-task Demonstrations »
  Konwoo Kim · Gokul Swamy · ZUXIN LIU · DING ZHAO · Sanjiban Choudhury · Steven Wu
• 2022 Poster: On Privacy and Personalization in Cross-Silo Federated Learning »
  Ken Liu · Shengyuan Hu · Steven Wu · Virginia Smith
• 2022 Poster: Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints »
  Justin Whitehouse · Aaditya Ramdas · Steven Wu · Ryan Rogers
• 2022 Poster: Incentivizing Combinatorial Bandit Exploration »
  Xinyan Hu · Dung Ngo · Aleksandrs Slivkins · Steven Wu
• 2022 Poster: Sequence Model Imitation Learning with Unobserved Contexts »
  Gokul Swamy · Sanjiban Choudhury · J. Bagnell · Steven Wu
• 2022 Poster: Private Synthetic Data for Multitask Learning and Marginal Queries »
  Giuseppe Vietri · Cedric Archambeau · Sergul Aydore · William Brown · Michael Kearns · Aaron Roth · Ankit Siva · Shuai Tang · Steven Wu
• 2022 Poster: Minimax Optimal Online Imitation Learning via Replay Estimation »
  Gokul Swamy · Nived Rajaraman · Matt Peng · Sanjiban Choudhury · J. Bagnell · Steven Wu · Jiantao Jiao · Kannan Ramchandran
• 2022 Poster: Provably sample-efficient RL with side information about latent dynamics »
  Yao Liu · Dipendra Misra · Miro Dudik · Robert Schapire
• 2022 Poster: Bayesian Persuasion for Algorithmic Recourse »
  Keegan Harris · Valerie Chen · Joon Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu
• 2021 : Leveraging strategic interactions for causal discovery »
  Steven Wu
• 2021 : Bayesian Persuasion for Algorithmic Recourse »
  Keegan Harris · Valerie Chen · Joon Sik Kim · Ameet Talwalkar · Hoda Heidari · Steven Wu
• 2021 : What Would the Expert do()?: Causal Imitation Learning »
  Gokul Swamy · Sanjiban Choudhury · James Bagnell · Steven Wu
• 2021 Poster: Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods »
  Terrance Liu · Giuseppe Vietri · Steven Wu
• 2021 Poster: Stateful Strategic Regression »
  Keegan Harris · Hoda Heidari · Steven Wu
• 2021 Poster: Bayesian decision-making under misspecified priors with applications to meta-learning »
  Max Simchowitz · Christopher Tosh · Akshay Krishnamurthy · Daniel Hsu · Thodoris Lykouris · Miro Dudik · Robert Schapire
• 2020 Poster: Metric-Free Individual Fairness in Online Learning »
  Yahav Bechavod · Christopher Jung · Steven Wu
• 2020 Poster: Understanding Gradient Clipping in Private SGD: A Geometric Perspective »
  Xiangyi Chen · Steven Wu · Mingyi Hong
• 2020 Poster: Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms »
  Xiangyi Chen · Tiancong Chen · Haoran Sun · Steven Wu · Mingyi Hong
• 2020 Spotlight: Understanding Gradient Clipping in Private SGD: A Geometric Perspective »
  Xiangyi Chen · Steven Wu · Mingyi Hong
• 2020 Oral: Metric-Free Individual Fairness in Online Learning »
  Yahav Bechavod · Christopher Jung · Steven Wu
• 2020 Poster: Constrained episodic reinforcement learning in concave-convex and knapsack settings »
  Kianté Brantley · Miro Dudik · Thodoris Lykouris · Sobhan Miryoosefi · Max Simchowitz · Aleksandrs Slivkins · Wen Sun
• 2019 Poster: Equal Opportunity in Online Classification with Partial Feedback »
  Yahav Bechavod · Katrina Ligett · Aaron Roth · Bo Waggoner · Steven Wu
• 2019 Poster: Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond »
  Arindam Banerjee · Qilong Gu · Vidyashankar Sivakumar · Steven Wu
• 2019 Poster: Private Hypothesis Selection »
  Mark Bun · Gautam Kamath · Thomas Steinke · Steven Wu
• 2019 Poster: Reinforcement Learning with Convex Constraints »
  Sobhan Miryoosefi · Kianté Brantley · Hal Daumé III · Miro Dudik · Robert Schapire
• 2019 Poster: Locally Private Gaussian Estimation »
  Matthew Joseph · Janardhan Kulkarni · Jieming Mao · Steven Wu
• 2017 : Spotlights »
  Antti Kangasrääsiö · Richard Everett · Yitao Liang · Yang Cai · Steven Wu · Vidya Muthukumar · Sven Schmit
• 2017 Poster: Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM »
  Katrina Ligett · Seth Neel · Aaron Roth · Bo Waggoner · Steven Wu
• 2017 Poster: Off-policy evaluation for slate recommendation »
  Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
• 2017 Poster: A Decomposition of Forecast Error in Prediction Markets »
  Miro Dudik · Sebastien Lahaie · Ryan Rogers · Jennifer Wortman Vaughan
• 2017 Oral: Off-policy evaluation for slate recommendation »
  Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
• 2016 Poster: Contextual semibandits via supervised learning oracles »
  Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik
• 2016 Poster: Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs »
  Shahin Jabbari · Ryan Rogers · Aaron Roth · Steven Wu
• 2014 Workshop: OPT2014: Optimization for Machine Learning »
  Zaid Harchaoui · Suvrit Sra · Alekh Agarwal · Martin Jaggi · Miro Dudik · Aaditya Ramdas · Jean Lasserre · Yoshua Bengio · Amir Beck