Simchowitz, Max

51 publications

ICLR 2025 Diffusion Policy Policy Optimization Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz

ICML 2025 History-Guided Video Diffusion Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann

NeurIPS 2025 Is Your Diffusion Model Actually Denoising? Daniel Pfrommer, Zehao Dou, Christopher Scarvelis, Max Simchowitz, Ali Jadbabaie

ICLR 2025 Self-Improvement in Language Models: The Sharpening Mechanism Audrey Huang, Adam Block, Dylan J Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy

COLT 2025 The Pitfalls of Imitation Learning When Actions Are Continuous Max Simchowitz, Daniel Pfrommer, Ali Jadbabaie

ICLR 2024 Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression Adam Block, Dylan J Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang

NeurIPS 2024 Diffusion Forcing: Next-Token Prediction Meets Full-Sequence Diffusion Boyuan Chen, Diego Martí Monsó, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann

ICLR 2024 Robot Fleet Learning via Policy Merging Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake

NeurIPSW 2024 Self-Improvement in Language Models: The Sharpening Mechanism Audrey Huang, Adam Block, Dylan J Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy

ICLR 2023 Learning to Extrapolate: A Transductive Approach Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

ICMLW 2023 On the Imitation of Non-Markovian Demonstrations: From Low-Level Stability to High-Level Planning Adam Block, Daniel Pfrommer, Max Simchowitz

COLT 2023 Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making Adam Block, Max Simchowitz, Alexander Rakhlin

NeurIPS 2023 Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake

NeurIPS 2023 RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta

NeurIPS 2023 Smoothed Online Learning for Prediction in Piecewise Affine Systems Adam Block, Max Simchowitz, Russ Tedrake

ICML 2023 Statistical Learning Under Heterogeneous Distribution Shift Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy

COLT 2023 Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective Max Simchowitz, Abhishek Gupta, Kaiqing Zhang

ICML 2023 The Power of Learned Locally Linear Models for Nonlinear Policy Optimization Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu

COLT 2022 Beyond No Regret: Instance-Dependent PAC Reinforcement Learning Andrew J Wagenmaker, Max Simchowitz, Kevin Jamieson

ICML 2022 Do Differentiable Simulators Give Better Policy Gradients? Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake

NeurIPS 2022 Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions Adam Block, Max Simchowitz

ICML 2022 First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach Andrew J Wagenmaker, Yifang Chen, Max Simchowitz, Simon Du, Kevin Jamieson

NeurIPS 2022 Globally Convergent Policy Search for Output Estimation Jack Umenberger, Max Simchowitz, Juan Perdomo, Kaiqing Zhang, Russ Tedrake

NeurIPSW 2022 Learning to Extrapolate: A Transductive Approach Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal

ICML 2022 Reward-Free RL Is No Harder than Reward-Aware RL in Linear Markov Decision Processes Andrew J Wagenmaker, Yifang Chen, Max Simchowitz, Simon Du, Kevin Jamieson

NeurIPS 2021 Bayesian Decision-Making Under Misspecified Priors with Applications to Meta-Learning Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miro Dudik, Robert E. Schapire

COLT 2021 Corruption-Robust Exploration in Episodic Reinforcement Learning Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun

NeurIPS 2021 Online Control of Unknown Time-Varying Dynamical Systems Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan

NeurIPS 2021 Stabilizing Dynamical Systems via Policy Gradient Methods Juan Perdomo, Jack Umenberger, Max Simchowitz

ICML 2021 Task-Optimal Exploration in Linear Dynamical Systems Andrew J Wagenmaker, Max Simchowitz, Kevin Jamieson

COLT 2021 Towards a Dimension-Free Understanding of Adaptive Linear Control Juan C Perdomo, Max Simchowitz, Alekh Agarwal, Peter Bartlett

ICML 2020 Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Bjorkegren, Moritz Hardt, Joshua Blumenstock

NeurIPS 2020 Constrained Episodic Reinforcement Learning in Concave-Convex and Knapsack Settings Kianté Brantley, Miro Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun

COLT 2020 Improper Learning for Non-Stochastic Control Max Simchowitz, Karan Singh, Elad Hazan

NeurIPS 2020 Learning the Linear Quadratic Regulator from Nonlinear Observations Zakaria Mhammedi, Dylan J Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford

ICML 2020 Logarithmic Regret for Adversarial Online Control Dylan Foster, Max Simchowitz

NeurIPS 2020 Making Non-Stochastic Control (Almost) as Easy as Stochastic Max Simchowitz

ICML 2020 Naive Exploration Is Optimal for Online LQR Max Simchowitz, Dylan Foster

ICML 2020 Reward-Free Exploration for Reinforcement Learning Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu

COLT 2020 The Gradient Complexity of Linear Regression Mark Braverman, Elad Hazan, Max Simchowitz, Blake Woodworth

IJCAI 2019 Delayed Impact of Fair Machine Learning Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

COLT 2019 Learning Linear Dynamical Systems with Semi-Parametric Least Squares Max Simchowitz, Ross Boczar, Benjamin Recht

NeurIPS 2019 Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs Max Simchowitz, Kevin G. Jamieson

ICML 2019 The Implicit Fairness Criterion of Unconstrained Learning Lydia T. Liu, Max Simchowitz, Moritz Hardt

AISTATS 2018 Approximate Ranking from Pairwise Comparisons Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright

ICML 2018 Delayed Impact of Fair Machine Learning Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

COLT 2018 Learning Without Mixing: Towards a Sharp Analysis of Linear System Identification Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht

COLT 2017 The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime Max Simchowitz, Kevin Jamieson, Benjamin Recht

COLT 2016 Best-of-K-Bandits Max Simchowitz, Kevin G. Jamieson, Benjamin Recht

COLT 2016 Gradient Descent Only Converges to Minimizers Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht

ICML 2016 Low-Rank Solutions of Linear Matrix Equations via Procrustes Flow Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht