Max Simchowitz
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
37
Venues
7
Active years
2016–2025
Best venue rank
A*
Where they publish
Papers
37 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | COLT | The title of the paper. | Max Simchowitz, Daniel Pfrommer, Ali Jadbabaie |
| 2025 | ICLR | 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 |
| 2025 | ICLR | Diffusion Policy Policy Optimization. | Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz |
| 2025 | ICML | History-Guided Video Diffusion. | Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann |
| 2025 | ICRA | Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans? | Yuki Shirai, Tong Zhao, H. J. Terry Suh, Huaijiang Zhu, Xinpei Ni, Jiuguang Wang, Max Simchowitz, Tao Pang |
| 2024 | ICLR | Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. | Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang |
| 2024 | ICLR | Robot Fleet Learning via Policy Merging. | Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake |
| 2024 | ICRA | Constrained Bimanual Planning with Analytic Inverse Kinematics. | Thomas Cohn, Seiji Shaw, Max Simchowitz, Russ Tedrake |
| 2023 | COLT | Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making. | Adam Block, Max Simchowitz, Alexander Rakhlin |
| 2023 | COLT | Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. | Max Simchowitz, Abhishek Gupta, Kaiqing Zhang |
| 2023 | ICLR | Learning to Extrapolate: A Transductive Approach. | Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal |
| 2023 | ICML | The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. | Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu |
| 2023 | ICML | Statistical Learning under Heterogenous Distribution Shift. | Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy |
| 2022 | COLT | Beyond No Regret: Instance-Dependent PAC Reinforcement Learning. | Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson |
| 2022 | ICML | Do Differentiable Simulators Give Better Policy Gradients? | Hyung Ju Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake |
| 2022 | ICML | First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach. | Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson |
| 2022 | ICML | Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes. | Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson |
| 2021 | COLT | Corruption-robust exploration in episodic reinforcement learning. | Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun |
| 2021 | COLT | Towards a Dimension-Free Understanding of Adaptive Linear Control. | Juan C. Perdomo, Max Simchowitz, Alekh Agarwal, Peter L. Bartlett |
| 2021 | ICML | Task-Optimal Exploration in Linear Dynamical Systems. | Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson |
| 2020 | COLT | The Gradient Complexity of Linear Regression. | Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth |
| 2020 | COLT | Improper Learning for Non-Stochastic Control. | Max Simchowitz, Karan Singh, Elad Hazan |
| 2020 | ICML | Logarithmic Regret for Adversarial Online Control. | Dylan J. Foster, Max Simchowitz |
| 2020 | ICML | Reward-Free Exploration for Reinforcement Learning. | Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu |
| 2020 | ICML | Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. | Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Bjrkegren, Moritz Hardt, Joshua Blumenstock |
| 2020 | ICML | Naive Exploration is Optimal for Online LQR. | Max Simchowitz, Dylan J. Foster |
| 2019 | COLT | Learning Linear Dynamical Systems with Semi-Parametric Least Squares. | Max Simchowitz, Ross Boczar, Benjamin Recht |
| 2019 | ICML | The Implicit Fairness Criterion of Unconstrained Learning. | Lydia T. Liu, Max Simchowitz, Moritz Hardt |
| 2019 | IJCAI | Delayed Impact of Fair Machine Learning. | Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt |
| 2018 | AISTATS | Approximate ranking from pairwise comparisons. | Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright |
| 2018 | COLT | Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification. | Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht |
| 2018 | ICML | Delayed Impact of Fair Machine Learning. | Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt |
| 2018 | STOC | Tight query complexity lower bounds for PCA via finite sample deformed wigner law. | Max Simchowitz, Ahmed El Alaoui, Benjamin Recht |
| 2017 | COLT | The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime. | Max Simchowitz, Kevin Jamieson, Benjamin Recht |
| 2016 | COLT | Gradient Descent Only Converges to Minimizers. | Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht |
| 2016 | COLT | Best-of-K-bandits. | Max Simchowitz, Kevin Jamieson, Benjamin Recht |
| 2016 | ICML | Low-rank Solutions of Linear Matrix Equations via Procrustes Flow. | Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht |