Duchi, John C.

47 publications

JMLR 2024 Predictive Inference with Weak Supervision Maxime Cauchois, Suyash Gupta, Alnur Ali, John C. Duchi

COLT 2024 Universally Instance-Optimal Mechanisms for Private Statistical Estimation Hilal Asi, John C. Duchi, Saminul Haque, Zewei Li, Feng Ruan

NeurIPS 2023 Collaboratively Learning Linear Models with Structured Missing Data Chen Cheng, Gary Cheng, John C. Duchi

NeurIPS 2022 Subspace Recovery from Heterogeneous Data with Non-Isotropic Noise John C. Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar

NeurIPS 2021 Adapting to Function Difficulty and Growth Conditions in Private Optimization Hilal Asi, Daniel Levy, John C. Duchi

JMLR 2021 Knowing What You Know: Valid and Validated Confidence Sets in Multiclass and Multilabel Prediction Maxime Cauchois, Suyash Gupta, John C. Duchi

NeurIPS 2020 Conic Descent and Its Application to Memory-Efficient Optimization over Positive Semidefinite Matrices John C. Duchi, Oliver Hinder, Andrew Naber, Yinyu Ye

NeurIPS 2020 Instance-Optimality in Differential Privacy via Approximate Inverse Sensitivity Mechanisms Hilal Asi, John C. Duchi

NeurIPS 2020 Large-Scale Methods for Distributionally Robust Optimization Daniel Levy, Yair Carmon, John C. Duchi, Aaron Sidford

NeurIPS 2020 Minibatch Stochastic Approximate Proximal Point Methods Hilal Asi, Karan Chadha, Gary Cheng, John C. Duchi

NeurIPS 2020 Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha, Matthew O'Kelly, Russ Tedrake, John C. Duchi

COLT 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan

COLT 2019 A Rank-1 Sketch for Matrix Multiplicative Weights Yair Carmon, John C Duchi, Sidford Aaron, Tian Kevin

AISTATS 2019 Modeling Simple Structures and Geometry for Better Stochastic Optimization Algorithms Hilal Asi, John C. Duchi

NeurIPS 2019 Necessary and Sufficient Geometries for Gradient Methods Daniel Levy, John C. Duchi

NeurIPS 2019 Unlabeled Data Improves Adversarial Robustness Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, John C. Duchi, Percy Liang

NeurIPS 2018 Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems Yair Carmon, John C. Duchi

AISTATS 2018 Derivative Free Optimization via Repeated Classification Tatsunori Hashimoto, Steve Yadlowsky, John C. Duchi

NeurIPS 2018 Generalizing to Unseen Domains via Adversarial Data Augmentation Riccardo Volpi, Hongseok Namkoong, Ozan Sener, John C. Duchi, Vittorio Murino, Silvio Savarese

COLT 2018 Minimax Bounds on Stochastic Batched Convex Optimization John C. Duchi, Feng Ruan, Chulhee Yun

NeurIPS 2018 Scalable End-to-End Autonomous Vehicle Testing via Rare-Event Simulation Matthew O'Kelly, Aman Sinha, Hongseok Namkoong, Russ Tedrake, John C. Duchi

ICML 2017 Adaptive Sampling Probabilities for Non-Smooth Optimization Hongseok Namkoong, Aman Sinha, Steve Yadlowsky, John C. Duchi

NeurIPS 2017 Unsupervised Transformation Learning via Convex Relaxations Tatsunori B Hashimoto, Percy Liang, John C. Duchi

NeurIPS 2017 Variance-Based Regularization with Convex Objectives Hongseok Namkoong, John C. Duchi

ICML 2017 “Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford

NeurIPS 2016 Learning Kernels with Random Features Aman Sinha, John C. Duchi

NeurIPS 2016 Local Minimax Complexity of Stochastic Convex Optimization Sabyasachi Chatterjee, John C. Duchi, John Lafferty, Yuancheng Zhu

NeurIPS 2016 Stochastic Gradient Methods for Distributionally Robust Optimization with F-Divergences Hongseok Namkoong, John C. Duchi

NeurIPS 2015 Asynchronous Stochastic Convex Optimization: The Noise Is in the Noise and SGD Don't Care Sorathan Chaturapruek, John C. Duchi, Christopher Ré

COLT 2015 Minimax Rates for Memory-Bounded Sparse Linear Regression Jacob Steinhardt, John C. Duchi

JMLR 2013 Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, John C. Duchi, Martin J. Wainwright

COLT 2013 Divide and Conquer Kernel Ridge Regression Yuchen Zhang, John C. Duchi, Martin J. Wainwright

NeurIPS 2012 Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, Martin J. Wainwright, John C. Duchi

NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods Andre Wibisono, Martin J. Wainwright, Michael I. Jordan, John C. Duchi

NeurIPS 2012 Privacy Aware Learning Martin J. Wainwright, Michael I. Jordan, John C. Duchi

NeurIPS 2011 Distributed Delayed Stochastic Optimization Alekh Agarwal, John C. Duchi

COLT 2011 Oracle Inequalities for Computationally Budgeted Model Selection Alekh Agarwal, John C. Duchi, Peter L. Bartlett, Clement Levrard

COLT 2010 Adaptive Subgradient Methods for Online Learning and Stochastic Optimization John C. Duchi, Elad Hazan, Yoram Singer

COLT 2010 Composite Objective Mirror Descent John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Ambuj Tewari

NeurIPS 2010 Distributed Dual Averaging in Networks Alekh Agarwal, Martin J. Wainwright, John C. Duchi

ICML 2010 On the Consistency of Ranking Algorithms John C. Duchi, Lester W. Mackey, Michael I. Jordan

ICML 2009 Boosting with Structural Sparsity John C. Duchi, Yoram Singer

NeurIPS 2009 Efficient Learning Using Forward-Backward Splitting Yoram Singer, John C. Duchi

UAI 2008 Constrained Approximate Maximum Entropy Learning of Markov Random Fields Varun Ganapathi, David Vickrey, John C. Duchi, Daphne Koller

ICML 2008 Efficient Projections onto the L1-Ball for Learning in High Dimensions John C. Duchi, Shai Shalev-Shwartz, Yoram Singer, Tushar Chandra

UAI 2008 Projected Subgradient Methods for Learning Sparse Gaussians John C. Duchi, Stephen Gould, Daphne Koller

NeurIPS 2006 Using Combinatorial Optimization Within Max-Product Belief Propagation Daniel Tarlow, Gal Elidan, Daphne Koller, John C. Duchi