Michael Jordan

Automatically Adaptive Conformal Risk Control AISTATS 2025 Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy AISTATS 2025 A Primal-Dual Approach to Solving Variational Inequalities with General Constraints ICLR 2024 A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport AISTATS 2024 Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference ICML 2024 Classifier Calibration with ROC-Regularized Isotonic Regression AISTATS 2024 Collaborative Heterogeneous Causal Inference Beyond Meta-analysis ICML 2024 Delegating Data Collection in Decentralized Machine Learning AISTATS 2024 Incentivized Learning in Principal-Agent Bandit Games ICML 2024 Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF ICML 2024 On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry AISTATS 2024 Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics NeurIPS 2024 A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning ICLR 2023 An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit ALT 2023 Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback OSDI 2023 Deterministic Nonsmooth Nonconvex Optimization COLT 2023 Federated Conformal Predictors for Distributed Uncertainty Quantification ICML 2023 Modeling content creator incentives on algorithm-curated platforms ICLR 2023 Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization ICML 2023 Neural Dependencies Emerging From Learning Massive Categories CVPR 2023 Online Learning in Stackelberg Games with an Omniscient Follower ICML 2023 Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons ICML 2023 Solving Constrained Variational Inequalities via a First-order Interior Point-based Method ICLR 2023 Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization AISTATS 2022 Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging ICML 2022 Learning Competitive Equilibria in Exchange Economies with Bandit Feedback AISTATS 2022 No-Regret Learning in Partially-Informed Auctions ICML 2022 Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback ICML 2022 On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms AISTATS 2022 On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging AISTATS 2022 Optimal Mean Estimation without a Variance COLT 2022 Partial Identification with Noisy Covariates: A Robust Optimization Approach CLeaR 2022 ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm COLT 2022 Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy ICML 2022 Provable Meta-Learning of Linear Representations ICML 2021 Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data ICML 2021 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism ICML 2021 Stochastic Approximation for Online Tensorial Independent Component Analysis COLT 2021 Uncertainty Sets for Image Classifiers using Conformal Prediction ICLR 2021 Accelerated Message Passing for Entropy-Regularized MAP Inference ICML 2020 Competing Bandits in Matching Markets AISTATS 2020 Continuous-time Lower Bounds for Gradient-based Algorithms ICML 2020 Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference AISTATS 2020 Cost-Effective Incentive Allocation via Structured Counterfactual Inference AAAI 2020 Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter AISTATS 2020 Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games ICML 2020 Learning to Score Behaviors for Guided Policy Optimization ICML 2020 LS-Tree: Model Interpretation When the Data Are Linguistic AAAI 2020 ML-LOO: Detecting Adversarial Examples with Feature Attribution AAAI 2020 On Approximate Thompson Sampling with Langevin Algorithms ICML 2020 On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems ICML 2020 Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models AISTATS 2020 Stochastic Gradient and Langevin Processes ICML 2020 The Power of Batching in Multiple Hypothesis Testing AISTATS 2020 What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization? ICML 2020 A Dynamical Systems Perspective on Nesterov Acceleration ICML 2019 A Swiss Army Infinitesimal Jackknife AISTATS 2019 Bridging Theory and Algorithm for Domain Adaptation ICML 2019 On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms ICML 2019 Probabilistic Multilevel Clustering via Composite Transportation Distance AISTATS 2019 Rao-Blackwellized Stochastic Gradients for Discrete Distributions ICML 2019 Theoretically Principled Trade-off between Robustness and Accuracy ICML 2019 Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation ICML 2019 Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers ICML 2019 Learning to Explain: An Information-Theoretic Perspective on Model Interpretation ICML 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 RLlib: Abstractions for Distributed Reinforcement Learning ICML 2018 SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate ICML 2018 Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017 A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016 A Linearly-Convergent Stochastic L-BFGS Algorithm AISTATS 2016 Adding vs. Averaging in Distributed Primal-Dual Optimization ICML 2015 A General Analysis of the Convergence of ADMM ICML 2015 Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds ICML 2015 Learning Transferable Features with Deep Adaptation Networks ICML 2015 Trust Region Policy Optimization ICML 2015 Efficient Ranking from Pairwise Comparisons ICML 2013 MAD-Bayes: MAP-based Asymptotic Derivations from Bayes ICML 2013 Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012 Learning Dependency-Based Compositional Semantics ACL 2011 Learning Semantic Correspondences with Less Supervision ACL 2009 The Infinite PCFG Using Hierarchical Dirichlet Processes EMNLP 2007 Coherence Functions for Multicategory Margin-based Classification Methods AISTATS 2005