Lipton, Zachary

37 publications

NeurIPS 2024 A Theoretical Case-Study of Scalable Oversight in Hierarchical Reinforcement Learning Tom Yan, Zachary Lipton

AISTATS 2024 Auditing Fairness Under Unobserved Confounding Yewon Byun, Dylan Sam, Michael Oberst, Zachary Lipton, Bryan Wilder

ALT 2024 Partially Interpretable Models with Guarantees on Coverage and Accuracy Nave Frost, Zachary Lipton, Yishay Mansour, Michal Moshkovitz

NeurIPS 2024 Post-Hoc Reversal: Are We Selecting Models Prematurely? Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Lipton

AISTATS 2024 Timing as an Action: Learning When to Observe and Act Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary Lipton

NeurIPS 2023 Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift Saurabh Garg, Amrith Setlur, Zachary Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan

NeurIPS 2023 Deep Equilibrium Based Neural Operators for Steady-State PDEs Tanya Marwah, Ashwini Pokle, J. Zico Kolter, Zachary Lipton, Jianfeng Lu, Andrej Risteski

AISTATS 2023 Domain Adaptation Under Missingness Shift Helen Zhou, Sivaraman Balakrishnan, Zachary Lipton

CHIL 2023 Evaluating Model Performance in Medical Datasets over Time Helen Zhou, Yuwen Chen, Zachary Lipton

NeurIPSW 2023 For Distillation, Tokens Are Not All You Need Mrigank Raman, Pranav Mani, Davis Liang, Zachary Lipton

NeurIPS 2023 Online Label Shift: Optimal Dynamic Regret Meets Practical Algorithms Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary Lipton, Yu-Xiang Wang

UAI 2023 Risk-Limiting Financial Audits via Weighted Sampling Without Replacement Shubhanshu Shekhar, Ziyu Xu, Zachary Lipton, Pierre Liang, Aaditya Ramdas

AISTATS 2022 Off-Policy Risk Assessment for Markov Decision Processes Audrey Huang, Liu Leqi, Zachary Lipton, Kamyar Azizzadenesheli

NeurIPS 2022 Characterizing Datapoints via Second-Split Forgetting Pratyush Maini, Saurabh Garg, Zachary Lipton, J. Zico Kolter

NeurIPS 2022 Domain Adaptation Under Open Set Label Shift Saurabh Garg, Sivaraman Balakrishnan, Zachary Lipton

ICML 2022 Supervised Learning with General Risk Functionals Liu Leqi, Audrey Huang, Zachary Lipton, Kamyar Azizzadenesheli

NeurIPS 2022 Unsupervised Learning Under Latent Label Shift Manley Roberts, Pranav Mani, Saurabh Garg, Zachary Lipton

AISTATS 2021 Causal Inference with Selectively Deconfounded Data Kyra Gan, Andrew Li, Zachary Lipton, Sridhar Tayur

ICML 2021 Correcting Exposure Bias for Link Recommendation Shantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang

NeurIPS 2021 Efficient Online Estimation of Causal Effects by Deciding What to Observe Shantanu Gupta, Zachary Lipton, David Childers

NeurIPS 2021 Mixture Proportion Estimation and PU Learning:A Modern Approach Saurabh Garg, Yifan Wu, Alexander J Smola, Sivaraman Balakrishnan, Zachary Lipton

NeurIPS 2021 Off-Policy Risk Assessment in Contextual Bandits Audrey Huang, Liu Leqi, Zachary Lipton, Kamyar Azizzadenesheli

ICML 2021 On Proximal Policy Optimization’s Heavy-Tailed Gradients Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

NeurIPS 2021 Parametric Complexity Bounds for Approximating PDEs with Neural Networks Tanya Marwah, Zachary Lipton, Andrej Risteski

ICML 2021 RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton

NeurIPS 2021 Rebounding Bandits for Modeling Satiation Effects Liu Leqi, Fatma Kilinc Karzan, Zachary Lipton, Alan Montgomery

NeurIPS 2020 A Unified View of Label Shift Estimation Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary Lipton

ICML 2020 Uncertainty-Aware Lookahead Factor Models for Quantitative Investing Lakshay Chauhan, John Alberg, Zachary Lipton

ICML 2019 Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment Yifan Wu, Ezra Winston, Divyansh Kaushik, Zachary Lipton

ICLRW 2019 Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment Yifan Wu, Ezra Winston, Divyansh Kaushik, Zachary Lipton

NeurIPS 2019 Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser, Stephan Günnemann, Zachary Lipton

NeurIPS 2019 Game Design for Eliciting Distinguishable Behavior Fan Yang, Liu Leqi, Yifan Wu, Zachary Lipton, Pradeep K Ravikumar, Tom M. Mitchell, William W. Cohen

NeurIPS 2019 Learning Robust Global Representations by Penalizing Local Predictive Power Haohan Wang, Songwei Ge, Zachary Lipton, Eric P Xing

ICML 2019 What Is the Effect of Importance Weighting in Deep Learning? Jonathon Byrd, Zachary Lipton

ICML 2018 Born Again Neural Networks Tommaso Furlanello, Zachary Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar

ICML 2018 Detecting and Correcting for Label Shift with Black Box Predictors Zachary Lipton, Yu-Xiang Wang, Alexander Smola

NeurIPS 2018 Does Mitigating ML's Impact Disparity Require Treatment Disparity? Zachary Lipton, Julian McAuley, Alexandra Chouldechova