ML Anthology

Wainwright, Martin J

83 publications

JMLR 2025 Instability, Computational Efficiency and Statistical Accuracy Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
ICMLW 2024 Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning Jia Wan, Sean R. Sinclair, Devavrat Shah, Martin J Wainwright
NeurIPS 2024 Taming "data-Hungry" Reinforcement Learning? Stability in Continuous State-Action Spaces Yaqi Duan, Martin J. Wainwright
L4DC 2023 A Finite-Sample Analysis of Multi-Step Temporal Difference Estimates Yaqi Duan, Martin J. Wainwright
JMLR 2023 Instance-Dependent Confidence and Early Stopping for Reinforcement Learning Eric Xia, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan
JMLR 2022 An Efficient Sampling Algorithm for Non-Smooth Composite Potentials Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
NeurIPS 2022 Bellman Residual Orthogonalization for Offline Reinforcement Learning Andrea Zanette, Martin J Wainwright
JMLR 2021 High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm Wenlong Mou, Yi-An Ma, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
NeurIPS 2021 Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette, Martin J Wainwright, Emma Brunskill
JMLR 2020 Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems Dhruv Malik, Ashwin Pananjady, Kush Bhatia, Koulik Khamaru, Peter L. Bartlett, Martin J. Wainwright
JMLR 2020 Fast Mixing of Metropolized Hamiltonian Monte Carlo: Benefits of Multi-Step Gradients Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
NeurIPS 2020 FedSplit: An Algorithmic Framework for Fast Federated Optimization Reese Pathak, Martin J. Wainwright
COLT 2020 On Linear Stochastic Approximation: Fine-Grained Polyak-Ruppert and Non-Asymptotic Concentration Wenlong Mou, Chris Junchi Li, Martin J Wainwright, Peter L Bartlett, Michael I Jordan
NeurIPS 2020 Preference Learning Along Multiple Criteria: A Game-Theoretic Perspective Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca Dragan, Martin J. Wainwright
JMLR 2019 Convergence Guarantees for a Class of Non-Convex and Non-Smooth Optimization Problems Koulik Khamaru, Martin J. Wainwright
ICLR 2019 L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data Jianbo Chen, Le Song, Martin J. Wainwright, Michael I. Jordan
JMLR 2019 Log-Concave Sampling: Metropolis-Hastings Algorithms Are Fast Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu
JMLR 2019 Low Permutation-Rank Matrices: Structural Properties and Noisy Completion Nihar B. Shah, Sivaraman Balakrishnan, Martin J. Wainwright
AISTATS 2018 Approximate Ranking from Pairwise Comparisons Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright
COLT 2018 Breaking the $1/\sqrt{n}$ Barrier: Faster Rates for Permutation-Based Models in Polynomial Time Cheng Mao, Ashwin Pananjady, Martin J. Wainwright
JMLR 2018 Fast MCMC Sampling Algorithms on Polytopes Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu
COLT 2018 Log-Concave Sampling: Metropolis-Hastings Algorithms Are Fast! Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu
NeurIPS 2018 Theoretical Guarantees for EM Under Misspecified Gaussian Mixture Models Raaz Dwivedi, Nhật Hồ, Koulik Khamaru, Martin J. Wainwright, Michael I Jordan
NeurIPS 2017 A Framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright
ICML 2017 Convexified Convolutional Neural Networks Yuchen Zhang, Percy Liang, Martin J. Wainwright
NeurIPS 2017 Early Stopping for Kernel Boosting Algorithms: A General Analysis with Localized Complexities Yuting Wei, Fanny Yang, Martin J. Wainwright
NeurIPS 2017 Kernel Feature Selection via Conditional Covariance Minimization Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I Jordan
AISTATS 2017 On the Learnability of Fully-Connected Neural Networks Yuchen Zhang, Jason D. Lee, Martin J. Wainwright, Michael I. Jordan
NeurIPS 2017 Online Control of the False Discovery Rate with Decaying Memory Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I Jordan
JMLR 2017 Statistical and Computational Guarantees for the Baum-Welch Algorithm Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright
JMLR 2016 A Practical Scheme and Fast Algorithm to Tune the Lasso with Optimality Guarantees Michael Chichignoud, Johannes Lederer, Martin J. Wainwright
JMLR 2016 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence Nihar B. Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright
JMLR 2016 Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares Mert Pilanci, Martin J. Wainwright
NeurIPS 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences Chi Jin, Yuchen Zhang, Sivaraman Balakrishnan, Martin J. Wainwright, Michael I Jordan
AISTATS 2015 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence Nihar B. Shah, Sivaraman Balakrishnan, Joseph K. Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright
JMLR 2015 Regularized M-Estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima Po-Ling Loh, Martin J. Wainwright
JMLR 2014 Early Stopping and Non-Parametric Regression: An Optimal Data-Dependent Stopping Rule Garvesh Raskutti, Martin J. Wainwright, Bin Yu
COLT 2014 Lower Bounds on the Performance of Polynomial-Time Algorithms for Sparse Linear Regression Yuchen Zhang, Martin J. Wainwright, Michael I. Jordan
JMLR 2013 Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees Nima Noorshams, Martin J. Wainwright
JMLR 2013 Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, John C. Duchi, Martin J. Wainwright
COLT 2013 Divide and Conquer Kernel Ridge Regression Yuchen Zhang, John C. Duchi, Martin J. Wainwright
NeurIPS 2013 Information-Theoretic Lower Bounds for Distributed Statistical Estimation with Communication Constraints Yuchen Zhang, John Duchi, Michael I Jordan, Martin J. Wainwright
NeurIPS 2013 Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation John Duchi, Martin J. Wainwright, Michael I Jordan
NeurIPS 2013 Regularized M-Estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima Po-Ling Loh, Martin J. Wainwright
NeurIPS 2012 Communication-Efficient Algorithms for Statistical Optimization Yuchen Zhang, Martin J. Wainwright, John C. Duchi
NeurIPS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods Andre Wibisono, Martin J. Wainwright, Michael I. Jordan, John C. Duchi
JMLR 2012 Minimax-Optimal Rates for Sparse Additive Models over Kernel Classes via Convex Programming Garvesh Raskutti, Martin J. Wainwright, Bin Yu
NeurIPS 2012 Privacy Aware Learning Martin J. Wainwright, Michael I. Jordan, John C. Duchi
JMLR 2012 Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise Sahand Negahban, Martin J. Wainwright
NeurIPS 2012 Stochastic Optimization and Sparse Statistical Recovery: Optimal Algorithms for High Dimensions Alekh Agarwal, Sahand Negahban, Martin J. Wainwright
NeurIPS 2012 Structure Estimation for Discrete Graphical Models: Generalized Covariance Matrices and Their Inverses Po-ling Loh, Martin J. Wainwright
NeurIPS 2011 A More Powerful Two-Sample Test in High Dimensions Using Random Projection Miles Lopes, Laurent Jacob, Martin J. Wainwright
NeurIPS 2011 High-Dimensional Regression with Noisy and Missing Data: Provable Guarantees with Non-Convexity Po-ling Loh, Martin J. Wainwright
ICML 2011 Noisy Matrix Decomposition via Convex Relaxation: Optimal Rates in High Dimensions Alekh Agarwal, Sahand N. Negahban, Martin J. Wainwright
NeurIPS 2010 Distributed Dual Averaging in Networks Alekh Agarwal, Martin J. Wainwright, John C. Duchi
ICML 2010 Estimation of (near) Low-Rank Matrices with Noise and High-Dimensional Scaling Sahand N. Negahban, Martin J. Wainwright
NeurIPS 2010 Fast Global Convergence Rates of Gradient Methods for High-Dimensional Statistical Recovery Alekh Agarwal, Sahand Negahban, Martin J. Wainwright
JMLR 2010 High-Dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency Dapo Omidiran, Martin J. Wainwright
JMLR 2010 Message-Passing for Graph-Structured Linear Programs: Proximal Methods and Rounding Schemes Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright
JMLR 2010 Restricted Eigenvalue Properties for Correlated Gaussian Designs Garvesh Raskutti, Martin J. Wainwright, Bin Yu
NeurIPS 2009 A Unified Framework for High-Dimensional Analysis of $m$-Estimators with Decomposable Regularizers Sahand Negahban, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar
NeurIPS 2009 Information-Theoretic Lower Bounds on the Oracle Complexity of Convex Optimization Alekh Agarwal, Martin J. Wainwright, Peter L. Bartlett, Pradeep K. Ravikumar
NeurIPS 2009 Lower Bounds on Minimax Rates for Nonparametric Regression with Additive Sparsity and Smoothness Garvesh Raskutti, Bin Yu, Martin J. Wainwright
FnTML 2008 Graphical Models, Exponential Families, and Variational Inference Martin J. Wainwright, Michael I. Jordan
NeurIPS 2008 High-Dimensional Support Union Recovery in Multivariate Regression Guillaume R. Obozinski, Martin J. Wainwright, Michael I. Jordan
ICML 2008 Message-Passing for Graph-Structured Linear Programs: Proximal Projections, Convergence and Rounding Schemes Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwright
NeurIPS 2008 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-Regularized MLE Garvesh Raskutti, Bin Yu, Martin J. Wainwright, Pradeep K. Ravikumar
NeurIPS 2008 Phase Transitions for High-Dimensional Joint Support Recovery Sahand Negahban, Martin J. Wainwright
NeurIPS 2007 Estimating Divergence Functionals and the Likelihood Ratio by Penalized Convex Risk Minimization Xuanlong Nguyen, Martin J. Wainwright, Michael I. Jordan
NeurIPS 2007 Loop Series and Bethe Variational Bounds in Attractive Graphical Models Alan S. Willsky, Erik B. Sudderth, Martin J. Wainwright
JMLR 2006 Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting Martin J. Wainwright
NeurIPS 2006 High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression Martin J. Wainwright, John D. Lafferty, Pradeep K. Ravikumar
NeurIPS 2005 Divergences, Surrogate Loss Functions and Experimental Design Xuanlong Nguyen, Martin J. Wainwright, Michael I. Jordan
NeurIPS 2005 Estimating the Wrong Markov Random Field: Benefits in the Computation-Limited Setting Martin J. Wainwright
UAI 2005 On the Optimality of Tree-Reweighted Max-Product Message-Passing Vladimir Kolmogorov, Martin J. Wainwright
ICML 2004 Decentralized Detection and Classification Using Kernel Methods XuanLong Nguyen, Martin J. Wainwright, Michael I. Jordan
NeurIPS 2003 Semidefinite Relaxations for Approximate Inference on Graphs with Cycles Michael I. Jordan, Martin J. Wainwright
AISTATS 2003 Tree-Reweighted Belief Propagation Algorithms and Approximate ML Estimation by Pseudo-Moment Matching Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
UAI 2002 A New Class of Upper Bounds on the Log Partition Function Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
NeurIPS 2002 Exact MAP Estimates by (Hyper)tree Agreement Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky
NeurIPS 2001 Tree-Based Reparameterization for Approximate Inference on Loopy Graphs Martin J. Wainwright, Tommi Jaakkola, Alan S. Willsky
NeurIPS 2000 Tree-Based Modeling and Estimation of Gaussian Processes on Graphs with Cycles Martin J. Wainwright, Erik B. Sudderth, Alan S. Willsky
NeurIPS 1999 Scale Mixtures of Gaussians and the Statistics of Natural Images Martin J. Wainwright, Eero P. Simoncelli