← Authors

John C. Duchi

35 papers · 2006–2024 · 5 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (5) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (19) πŸƒ Academic Marathon (18) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (26) πŸ† Keyword Champion πŸ”¬ Deep Specialist (19) πŸ’Ž Century Club (35) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (62) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (10)

Conferences

NIPS (26) COLT (3) JMLR (3) ICML (2) AISTATS (1)

Top co-authors

Yair Carmon (5) Martin J. Wainwright (5) Hilal Asi (5) Hongseok Namkoong (5) Aman Sinha (4) Daniel Levy (3) Alekh Agarwal (3) Oliver Hinder (2) Suyash Gupta (2) Maxime Cauchois (2)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

convex optimization (8) stochastic optimization (6) distributed optimization (4) stochastic convex optimization (4) differential privacy (4) stochastic gradient descent (4) gradient descent (4) convergence rate (4) stochastic gradient (3) distributionally robust optimization (3) empirical risk minimization (3) statistical optimization (2) asynchronous optimization (2) conformal prediction (2) communication-efficient algorithms (2) semi-supervised learning (2) statistical estimation (2) linear regression (2) principal component analysis (2) non-convex optimization (2)

Papers

Universally Instance-Optimal Mechanisms for Private Statistical Estimation COLT 2024
Predictive Inference with Weak Supervision JMLR 2024
Collaboratively Learning Linear Models with Structured Missing Data NIPS 2023
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise NIPS 2022
Adapting to function difficulty and growth conditions in private optimization NIPS 2021
Knowing what You Know: valid and validated confidence sets in multiclass and multilabel prediction JMLR 2021
Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices NIPS 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020
Minibatch Stochastic Approximate Proximal Point Methods NIPS 2020
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms NIPS 2020
Large-Scale Methods for Distributionally Robust Optimization NIPS 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems NIPS 2020
Necessary and Sufficient Geometries for Gradient Methods NIPS 2019
Unlabeled Data Improves Adversarial Robustness NIPS 2019
Modeling simple structures and geometry for better stochastic optimization algorithms AISTATS 2019
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation NIPS 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation NIPS 2018
Analysis of Krylov Subspace Solutions of Regularized Non-Convex Quadratic Problems NIPS 2018
Adaptive Sampling Probabilities for Non-Smooth Optimization ICML 2017
β€œConvex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions ICML 2017
Variance-based Regularization with Convex Objectives NIPS 2017
Unsupervised Transformation Learning via Convex Relaxations NIPS 2017
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NIPS 2016
Learning Kernels with Random Features NIPS 2016
Local Minimax Complexity of Stochastic Convex Optimization NIPS 2016
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care NIPS 2015
Communication-Efficient Algorithms for Statistical Optimization JMLR 2013
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NIPS 2012
Communication-Efficient Algorithms for Statistical Optimization NIPS 2012
Privacy Aware Learning NIPS 2012
Distributed Delayed Stochastic Optimization NIPS 2011
Oracle inequalities for computationally budgeted model selection COLT 2011
Distributed Dual Averaging In Networks NIPS 2010
Efficient Learning using Forward-Backward Splitting NIPS 2009
Using Combinatorial Optimization within Max-Product Belief Propagation NIPS 2006