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John Duchi

27 papers · 2009–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (14) 🌈 Renaissance Researcher (5) πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (116) πŸ“ˆ Trend Setter πŸ’Ž Century Club (27) πŸ”₯ Unstoppable (8) πŸš€ Conference Pioneer

Conferences

COLT (8) ICML (7) AISTATS (4) JMLR (4) NIPS (3) ICLR (1)

Top co-authors

Karan Chadha (3) Michael I Jordan (3) Michael I. Jordan (3) Gary Cheng (3) Yuchen Zhang (3) Chen Cheng (2) Saminul Haque (2) Aman Sinha (2) Martin J. Wainwright (2) Hongseok Namkoong (2)

Research topics

Privacy (1)

Keywords

lower bound (5) stochastic optimization (4) minimax rate (4) differential privacy (4) convergence rate (3) convex optimization (3) regret bound (3) distributed learning (3) statistical learning theory (2) information theory (2) mean estimation (2) divide and conquer (2) online learning (2) parameter estimation (2) sample complexity (2) statistical learning (2) communication complexity (2) kernel ridge regression (2) stochastic gradient descent (1) model misspecification (1)

Papers

Online Conformal Prediction via Online Optimization ICML 2025
An information-theoretic lower bound in time-uniform estimation COLT 2024
Two fundamental limits for uncertainty quantification in predictive inference COLT 2024
A Pretty Fast Algorithm for Adaptive Private Mean Estimation COLT 2023
Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023
Memorize to generalize: on the necessity of interpolation in high dimensional linear regression COLT 2022
Private optimization in the interpolation regime: faster rates and hardness results ICML 2022
Accelerated, Optimal and Parallel: Some results on model-based stochastic optimization ICML 2022
Misspecification in Prediction Problems and Robustness via Improper Learning AISTATS 2021
Private Adaptive Gradient Methods for Convex Optimization ICML 2021
A constrained risk inequality for general losses AISTATS 2021
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis ICML 2020
Understanding and Mitigating the Tradeoff between Robustness and Accuracy ICML 2020
Variance-based Regularization with Convex Objectives JMLR 2019
Lower Bounds for Locally Private Estimation via Communication Complexity COLT 2019
Minimax Bounds on Stochastic Batched Convex Optimization COLT 2018
Certifying Some Distributional Robustness with Principled Adversarial Training ICLR 2018
Derivative Free Optimization Via Repeated Classification AISTATS 2018
Estimation from Indirect Supervision with Linear Moments ICML 2016
Minimax rates for memory-bounded sparse linear regression COLT 2015
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates JMLR 2015
Estimation, Optimization, and Parallelism when Data is Sparse NIPS 2013
Divide and Conquer Kernel Ridge Regression COLT 2013
Information-theoretic lower bounds for distributed statistical estimation with communication constraints NIPS 2013
Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation NIPS 2013
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization JMLR 2011
Efficient Online and Batch Learning Using Forward Backward Splitting JMLR 2009