Duchi, John

28 publications

ICML 2025 Online Conformal Prediction via Online Optimization Felipe Areces, Christopher Mohri, Tatsunori Hashimoto, John Duchi

NeurIPS 2025 Sample-Conditional Coverage in Split-Conformal Prediction John Duchi

COLT 2024 An Information-Theoretic Lower Bound in Time-Uniform Estimation John Duchi, Saminul Haque

COLT 2024 Two Fundamental Limits for Uncertainty Quantification in Predictive Inference Felipe Areces, Chen Cheng, John Duchi, Kuditipudi Rohith

COLT 2023 A Pretty Fast Algorithm for Adaptive Private Mean Estimation Rohith Kuditipudi, John Duchi, Saminul Haque

ICMLW 2023 Differentially Private Heavy Hitters Using Federated Analytics Karan Chadha, Junye Chen, John Duchi, Vitaly Feldman, Hanieh Hashemi, Omid Javidbakht, Audra McMillan, Kunal Talwar

AISTATS 2023 Federated Asymptotics: A Model to Compare Federated Learning Algorithms Gary Cheng, Karan Chadha, John Duchi

ICML 2022 Accelerated, Optimal and Parallel: Some Results on Model-Based Stochastic Optimization Karan Chadha, Gary Cheng, John Duchi

COLT 2022 Memorize to Generalize: On the Necessity of Interpolation in High Dimensional Linear Regression Chen Cheng, John Duchi, Rohith Kuditipudi

ICML 2022 Private Optimization in the Interpolation Regime: Faster Rates and Hardness Results Hilal Asi, Karan Chadha, Gary Cheng, John Duchi

NeurIPSW 2022 adaStar: A Method for Adapting to Interpolation Gary Cheng, John Duchi

AISTATS 2021 A Constrained Risk Inequality for General Losses John Duchi, Feng Ruan

AISTATS 2021 Misspecification in Prediction Problems and Robustness via Improper Learning Annie Marsden, John Duchi, Gregory Valiant

ICML 2021 Private Adaptive Gradient Methods for Convex Optimization Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

NeurIPSW 2021 Private Confidence Sets Karan Chadha, John Duchi, Rohith Kuditipudi

ICML 2020 FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis Aman Sinha, Matthew O’Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake

ICML 2020 Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang

ICMLW 2019 Adversarial Training Can Hurt Generalization Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang

COLT 2019 Lower Bounds for Locally Private Estimation via Communication Complexity John Duchi, Ryan Rogers

JMLR 2019 Variance-Based Regularization with Convex Objectives John Duchi, Hongseok Namkoong

ICLR 2018 Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha, Hongseok Namkoong, John Duchi

ICML 2016 Estimation from Indirect Supervision with Linear Moments Aditi Raghunathan, Roy Frostig, John Duchi, Percy Liang

JMLR 2015 Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates Yuchen Zhang, John Duchi, Martin Wainwright

NeurIPS 2013 Estimation, Optimization, and Parallelism When Data Is Sparse John Duchi, Michael I Jordan, Brendan McMahan

NeurIPS 2013 Information-Theoretic Lower Bounds for Distributed Statistical Estimation with Communication Constraints Yuchen Zhang, John Duchi, Michael I Jordan, Martin J. Wainwright

NeurIPS 2013 Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation John Duchi, Martin J. Wainwright, Michael I Jordan

JMLR 2011 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John Duchi, Elad Hazan, Yoram Singer

JMLR 2009 Efficient Online and Batch Learning Using Forward Backward Splitting John Duchi, Yoram Singer