Michael Jordan

42 catalog papers. Name-matched publications do not establish a verified researcher identity.

Publications

• Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Instability, Computational Efficiency and Statistical Accuracy — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Desiderata for Representation Learning: A Causal Perspective — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
• Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
• First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Instance-Dependent Confidence and Early Stopping for Reinforcement Learning — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• On Learning Rates and Schrödinger Operators — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers? — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• On the Complexity of Approximating Multimarginal Optimal Transport — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Convergence Rates for Gaussian Mixtures of Experts — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• On the Efficiency of Entropic Regularized Algorithms for Optimal Transport — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Active Learning for Nonlinear System Identification with Guarantees — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• Asynchronous Online Testing of Multiple Hypotheses — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• Learning Strategies in Decentralized Matching Markets under Uncertain Preferences — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• Bandit Learning in Decentralized Matching Markets — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• A Lyapunov Analysis of Accelerated Methods in Optimization — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
• Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
• Covariances, Robustness, and Variational Bayes — Journal of Machine Learning Research 2018 (name-matched, not ORCID-linked)
• CoCoA: A General Framework for Communication-Efficient Distributed Optimization — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Saturating Splines and Feature Selection — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
• Distributed Matrix Completion and Robust Factorization — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
• Particle Gibbs with Ancestor Sampling — Journal of Machine Learning Research 2014 (name-matched, not ORCID-linked)
• EP-GIG Priors and Applications in Bayesian Sparse Learning — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• Coherence Functions with Applications in Large-Margin Classification Methods — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• Bayesian Generalized Kernel Mixed Models — Journal of Machine Learning Research 2011 (name-matched, not ORCID-linked)
• Regularized Discriminant Analysis, Ridge Regression and Beyond — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)
• Learning Spectral Clustering, With Application To Speech Separation — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Structured Prediction, Dual Extragradient and Bregman Projections — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Learning the Kernel Matrix with Semidefinite Programming — Journal of Machine Learning Research 2004 (name-matched, not ORCID-linked)
• Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces — Journal of Machine Learning Research 2004 (name-matched, not ORCID-linked)
• Beyond Independent Components: Trees and Clusters — Journal of Machine Learning Research 2003 (name-matched, not ORCID-linked)
• Matching Words and Pictures — Journal of Machine Learning Research 2002 (name-matched, not ORCID-linked)
• Latent Dirichlet Allocation — Journal of Machine Learning Research 2002 (name-matched, not ORCID-linked)
• A Robust Minimax Approach to Classification — Journal of Machine Learning Research 2002 (name-matched, not ORCID-linked)
• Kernel Independent Component Analysis — Journal of Machine Learning Research 2002 (name-matched, not ORCID-linked)
• Learning with Mixtures of Trees — Journal of Machine Learning Research 2000 (name-matched, not ORCID-linked)