Michael I Jordan

Nonconvex stochastic scaled gradient descent and generalized eigenvector problems UAI 2023 VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback JMLR 2023 On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration COLT 2020 Provably efficient reinforcement learning with linear function approximation COLT 2020 Acceleration via Symplectic Discretization of High-Resolution Differential Equations NeurIPS 2019 Transferable Normalization: Towards Improving Transferability of Deep Neural Networks NeurIPS 2019 Conditional Adversarial Domain Adaptation NeurIPS 2018 Generalized Zero-Shot Learning with Deep Calibration Network NeurIPS 2018 Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation NeurIPS 2018 Information Constraints on Auto-Encoding Variational Bayes NeurIPS 2018 Is Q-Learning Provably Efficient? NeurIPS 2018 On the Local Minima of the Empirical Risk NeurIPS 2018 Stochastic Cubic Regularization for Fast Nonconvex Optimization NeurIPS 2018 Theoretical guarantees for EM under misspecified Gaussian mixture models NeurIPS 2018 Fast Black-box Variational Inference through Stochastic Trust-Region Optimization NeurIPS 2017 Gradient Descent Can Take Exponential Time to Escape Saddle Points NeurIPS 2017 Kernel Feature Selection via Conditional Covariance Minimization NeurIPS 2017 Non-convex Finite-Sum Optimization Via SCSG Methods NeurIPS 2017 Online control of the false discovery rate with decaying memory NeurIPS 2017 Cyclades: Conflict-free Asynchronous Machine Learning NeurIPS 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NeurIPS 2016 Unsupervised Domain Adaptation with Residual Transfer Networks NeurIPS 2016 Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes NeurIPS 2015 On the Accuracy of Self-Normalized Log-Linear Models NeurIPS 2015 Parallel Correlation Clustering on Big Graphs NeurIPS 2015 Variational Consensus Monte Carlo NeurIPS 2015 Communication-Efficient Distributed Dual Coordinate Ascent NeurIPS 2014 On the Convergence Rate of Decomposable Submodular Function Minimization NeurIPS 2014 Parallel Double Greedy Submodular Maximization NeurIPS 2014 Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing NeurIPS 2014 A Comparative Framework for Preconditioned Lasso Algorithms NeurIPS 2013 Estimation, Optimization, and Parallelism when Data is Sparse NeurIPS 2013 Information-theoretic lower bounds for distributed statistical estimation with communication constraints NeurIPS 2013 Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation NeurIPS 2013 Optimistic Concurrency Control for Distributed Unsupervised Learning NeurIPS 2013 Streaming Variational Bayes NeurIPS 2013