Max Simchowitz

122 papers A* 49A 1Journal 68Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps. CoRR Peter Holderrieth, Douglas Chen, Luca Eyring, Ishin Shah, Giri Anantharaman, Yutong He, Zeynep Akata, Tommi S. Jaakkola, Nicholas Matthew Boffi, Max Simchowitz
2025	—	`conf`	A Test-Function Approach to Incremental Stability. CDC Daniel Pfrommer, Max Simchowitz, Ali Jadbabaie
2025	J	`jnl`	A Test-Function Approach to Incremental Stability. CoRR Daniel Pfrommer, Max Simchowitz, Ali Jadbabaie
2025	J	`jnl`	Corruption-Robust Exploration in Episodic Reinforcement Learning. Math. Oper. Res. Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2025	A*	`conf`	Diffusion Policy Policy Optimization. ICLR Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz
2025	A*	`conf`	History-Guided Video Diffusion. ICML Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann
2025	J	`jnl`	History-Guided Video Diffusion. CoRR Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann
2025	A*	`conf`	Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans? ICRA Yuki Shirai, Tong Zhao, H. J. Terry Suh, Huaijiang Zhu, Xinpei Ni, Jiuguang Wang, Max Simchowitz, Tao Pang
2025	J	`jnl`	Is Your Conditional Diffusion Model Actually Denoising? CoRR Daniel Pfrommer, Zehao Dou, Christopher Scarvelis, Max Simchowitz, Ali Jadbabaie
2025	J	`jnl`	Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models. CoRR Xinyue Ai, Yutong He, Albert Gu, Ruslan Salakhutdinov, J. Zico Kolter, Nicholas Matthew Boffi, Max Simchowitz
2025	J	`jnl`	Much Ado About Noising: Dispelling the Myths of Generative Robotic Control. CoRR Chaoyi Pan, Giri Anantharaman, Nai-Chieh Huang, Claire Jin, Daniel Pfrommer, Chenyang Yuan, Frank Permenter, Guannan Qu, Nicholas Boffi, Guanya Shi, Max Simchowitz
2025	J	`jnl`	Non-Euclidean motion planning with graphs of geodesically convex sets. Int. J. Robotics Res. Thomas Cohn, Mark Petersen, Max Simchowitz, Russ Tedrake
2025	A*	`conf`	Self-Improvement in Language Models: The Sharpening Mechanism. ICLR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2025	J	`jnl`	The Pitfalls of Imitation Learning when Actions are Continuous. CoRR Max Simchowitz, Daniel Pfrommer, Ali Jadbabaie
2025	A*	`conf`	The title of the paper. COLT Max Simchowitz, Daniel Pfrommer, Ali Jadbabaie
2025	J	`jnl`	e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs. CoRR Amrith Setlur, Matthew Y. R. Yang, Charlie Snell, Jeremy Greer, Ian Wu, Virginia Smith, Max Simchowitz, Aviral Kumar
2024	A*	`conf`	Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. ICLR Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
2024	A*	`conf`	Constrained Bimanual Planning with Analytic Inverse Kinematics. ICRA Thomas Cohn, Seiji Shaw, Max Simchowitz, Russ Tedrake
2024	A*	`conf`	Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. NeurIPS Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann
2024	J	`jnl`	Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. CoRR Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann
2024	J	`jnl`	Diffusion Policy Policy Optimization. CoRR Allen Z. Ren, Justin Lidard, Lars Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz
2024	J	`jnl`	Exploration and Incentives in Reinforcement Learning. Oper. Res. Max Simchowitz, Aleksandrs Slivkins
2024	J	`jnl`	Faster Algorithms for Growing Collision-Free Convex Polytopes in Robot Configuration Space. CoRR Peter Werner, Thomas Cohn, Rebecca H. Jiang, Tim Seyde, Max Simchowitz, Russ Tedrake, Daniela Rus
2024	J	`jnl`	Is Linear Feedback on Smoothed Dynamics Sufficient for Stabilizing Contact-Rich Plans? CoRR Yuki Shirai, Tong Zhao, H. J. Terry Suh, Huaijiang Zhu, Xinpei Ni, Jiuguang Wang, Max Simchowitz, Tao Pang
2024	A*	`conf`	Robot Fleet Learning via Policy Merging. ICLR Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake
2024	J	`jnl`	Self-Improvement in Language Models: The Sharpening Mechanism. CoRR Audrey Huang, Adam Block, Dylan J. Foster, Dhruv Rohatgi, Cyril Zhang, Max Simchowitz, Jordan T. Ash, Akshay Krishnamurthy
2023	J	`jnl`	Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression. CoRR Adam Block, Dylan J. Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
2023	J	`jnl`	Constrained Bimanual Planning with Analytic Inverse Kinematics. CoRR Thomas Cohn, Seiji Shaw, Max Simchowitz, Russ Tedrake
2023	J	`jnl`	Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use. CoRR Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake
2023	J	`jnl`	Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior. CoRR Adam Block, Daniel Pfrommer, Max Simchowitz
2023	A*	`conf`	Learning to Extrapolate: A Transductive Approach. ICLR Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal
2023	J	`jnl`	Learning to Extrapolate: A Transductive Approach. CoRR Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal
2023	—	`conf`	Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets. Robotics: Science and Systems Thomas Cohn, Mark Petersen, Max Simchowitz, Russ Tedrake
2023	J	`jnl`	Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets. CoRR Thomas Cohn, Mark Petersen, Max Simchowitz, Russ Tedrake
2023	A*	`conf`	Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making. COLT Adam Block, Max Simchowitz, Alexander Rakhlin
2023	J	`jnl`	Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making. CoRR Adam Block, Alexander Rakhlin, Max Simchowitz
2023	A*	`conf`	Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior. NeurIPS Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake
2023	A*	`conf`	RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. NeurIPS Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta
2023	J	`jnl`	RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. CoRR Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta
2023	A*	`conf`	Smoothed Online Learning for Prediction in Piecewise Affine Systems. NeurIPS Adam Block, Max Simchowitz, Russ Tedrake
2023	J	`jnl`	Smoothed Online Learning for Prediction in Piecewise Affine Systems. CoRR Adam Block, Max Simchowitz, Russ Tedrake
2023	A*	`conf`	Statistical Learning under Heterogenous Distribution Shift. ICML Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy
2023	J	`jnl`	Statistical Learning under Heterogenous Distribution Shift. CoRR Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy
2023	A*	`conf`	Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. COLT Max Simchowitz, Abhishek Gupta, Kaiqing Zhang
2023	J	`jnl`	Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. CoRR Max Simchowitz, Abhishek Gupta, Kaiqing Zhang
2023	A*	`conf`	The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. ICML Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu
2023	J	`jnl`	The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. CoRR Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu
2022	A*	`conf`	Beyond No Regret: Instance-Dependent PAC Reinforcement Learning. COLT Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson
2022	A*	`conf`	Do Differentiable Simulators Give Better Policy Gradients? ICML Hyung Ju Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake
2022	J	`jnl`	Do Differentiable Simulators Give Better Policy Gradients? CoRR H. J. Terry Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake
2022	A*	`conf`	Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions. NeurIPS Adam Block, Max Simchowitz
2022	J	`jnl`	Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions. CoRR Adam Block, Max Simchowitz
2022	A*	`conf`	First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach. ICML Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2022	A*	`conf`	Globally Convergent Policy Search for Output Estimation. NeurIPS Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake
2022	J	`jnl`	Globally Convergent Policy Search over Dynamic Filters for Output Estimation. CoRR Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake
2022	J	`jnl`	Online Control of Unknown Time-Varying Dynamical Systems. CoRR Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan
2022	A*	`conf`	Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes. ICML Andrew J. Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2022	J	`jnl`	Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes. CoRR Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2021	J	`jnl`	A Successive-Elimination Approach to Adaptive Robotic Source Seeking. IEEE Trans. Robotics Esther Rolf, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin
2021	A*	`conf`	Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	J	`jnl`	Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	J	`jnl`	Beyond No Regret: Instance-Dependent PAC Reinforcement Learning. CoRR Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
2021	A*	`conf`	Corruption-robust exploration in episodic reinforcement learning. COLT Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun
2021	J	`jnl`	Exploration and Incentives in Reinforcement Learning. CoRR Max Simchowitz, Aleksandrs Slivkins
2021	J	`jnl`	First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach. CoRR Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson
2021	—	`conf`	On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective. CDC Tyler Westenbroek, Max Simchowitz, Michael I. Jordan, S. Shankar Sastry
2021	J	`jnl`	On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective. CoRR Tyler Westenbroek, Max Simchowitz, Michael I. Jordan, S. Shankar Sastry
2021	A*	`conf`	Online Control of Unknown Time-Varying Dynamical Systems. NeurIPS Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan
2021	A*	`conf`	Stabilizing Dynamical Systems via Policy Gradient Methods. NeurIPS Juan C. Perdomo, Jack Umenberger, Max Simchowitz
2021	J	`jnl`	Stabilizing Dynamical Systems via Policy Gradient Methods. CoRR Juan C. Perdomo, Jack Umenberger, Max Simchowitz
2021	—	`—`	Statistical Complexity and Regret in Linear Control. Max Simchowitz
2021	A*	`conf`	Task-Optimal Exploration in Linear Dynamical Systems. ICML Andrew J. Wagenmaker, Max Simchowitz, Kevin Jamieson
2021	J	`jnl`	Task-Optimal Exploration in Linear Dynamical Systems. CoRR Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
2021	A*	`conf`	Towards a Dimension-Free Understanding of Adaptive Linear Control. COLT Juan C. Perdomo, Max Simchowitz, Alekh Agarwal, Peter L. Bartlett
2021	J	`jnl`	Towards a Dimension-Free Understanding of Adaptive Linear Control. CoRR Juan C. Perdomo, Max Simchowitz, Alekh Agarwal, Peter L. Bartlett
2020	A*	`conf`	Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. ICML Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock
2020	J	`jnl`	Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. CoRR Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock
2020	A*	`conf`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. NeurIPS Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	J	`jnl`	Constrained episodic reinforcement learning in concave-convex and knapsack settings. CoRR Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2020	A*	`conf`	Improper Learning for Non-Stochastic Control. COLT Max Simchowitz, Karan Singh, Elad Hazan
2020	J	`jnl`	Improper Learning for Non-Stochastic Control. CoRR Max Simchowitz, Karan Singh, Elad Hazan
2020	A*	`conf`	Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	J	`jnl`	Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	A*	`conf`	Logarithmic Regret for Adversarial Online Control. ICML Dylan J. Foster, Max Simchowitz
2020	J	`jnl`	Logarithmic Regret for Adversarial Online Control. CoRR Dylan J. Foster, Max Simchowitz
2020	A*	`conf`	Making Non-Stochastic Control (Almost) as Easy as Stochastic. NeurIPS Max Simchowitz
2020	J	`jnl`	Making Non-Stochastic Control (Almost) as Easy as Stochastic. CoRR Max Simchowitz
2020	A*	`conf`	Naive Exploration is Optimal for Online LQR. ICML Max Simchowitz, Dylan J. Foster
2020	J	`jnl`	Naive Exploration is Optimal for Online LQR. CoRR Max Simchowitz, Dylan J. Foster
2020	A*	`conf`	Reward-Free Exploration for Reinforcement Learning. ICML Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
2020	J	`jnl`	Reward-Free Exploration for Reinforcement Learning. CoRR Chi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu
2020	A*	`conf`	The Gradient Complexity of Linear Regression. COLT Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth
2019	J	`jnl`	Corruption Robust Exploration in Episodic Reinforcement Learning. CoRR Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun
2019	A*	`conf`	Delayed Impact of Fair Machine Learning. IJCAI Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt
2019	J	`jnl`	First-order methods almost always avoid strict saddle points. Math. Program. Jason D. Lee, Ioannis Panageas, Georgios Piliouras, Max Simchowitz, Michael I. Jordan, Benjamin Recht
2019	A*	`conf`	Learning Linear Dynamical Systems with Semi-Parametric Least Squares. COLT Max Simchowitz, Ross Boczar, Benjamin Recht
2019	J	`jnl`	Learning Linear Dynamical Systems with Semi-Parametric Least Squares. CoRR Max Simchowitz, Ross Boczar, Benjamin Recht
2019	A*	`conf`	Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs. NeurIPS Max Simchowitz, Kevin Jamieson
2019	J	`jnl`	Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs. CoRR Max Simchowitz, Kevin Jamieson
2019	A*	`conf`	The Implicit Fairness Criterion of Unconstrained Learning. ICML Lydia T. Liu, Max Simchowitz, Moritz Hardt
2019	J	`jnl`	The gradient complexity of linear regression. CoRR Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth
2018	J	`jnl`	A Successive-Elimination Approach to Adaptive Robotic Sensing. CoRR Esther Rolf, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin
2018	J	`jnl`	Adaptive Sampling for Convex Regression. CoRR Max Simchowitz, Kevin Jamieson, Jordan W. Suchow, Thomas L. Griffiths
2018	J	`jnl`	Approximate Ranking from Pairwise Comparisons. CoRR Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright
2018	A	`conf`	Approximate ranking from pairwise comparisons. AISTATS Reinhard Heckel, Max Simchowitz, Kannan Ramchandran, Martin J. Wainwright
2018	A*	`conf`	Delayed Impact of Fair Machine Learning. ICML Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt
2018	J	`jnl`	Delayed Impact of Fair Machine Learning. CoRR Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt
2018	J	`jnl`	Group calibration is a byproduct of unconstrained learning. CoRR Lydia T. Liu, Max Simchowitz, Moritz Hardt
2018	A*	`conf`	Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification. COLT Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht
2018	J	`jnl`	Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification. CoRR Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht
2018	J	`jnl`	On the Randomized Complexity of Minimizing a Convex Quadratic Function. CoRR Max Simchowitz
2018	J	`jnl`	Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law. CoRR Max Simchowitz, Ahmed El Alaoui, Benjamin Recht
2018	A*	`conf`	Tight query complexity lower bounds for PCA via finite sample deformed wigner law. STOC Max Simchowitz, Ahmed El Alaoui, Benjamin Recht
2017	J	`jnl`	First-order Methods Almost Always Avoid Saddle Points. CoRR Jason D. Lee, Ioannis Panageas, Georgios Piliouras, Max Simchowitz, Michael I. Jordan, Benjamin Recht
2017	J	`jnl`	On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation. CoRR Max Simchowitz, Ahmed El Alaoui, Benjamin Recht
2017	A*	`conf`	The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime. COLT Max Simchowitz, Kevin Jamieson, Benjamin Recht
2017	J	`jnl`	The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime. CoRR Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016	J	`jnl`	Best-of-K Bandits. CoRR Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016	A*	`conf`	Best-of-K-bandits. COLT Max Simchowitz, Kevin Jamieson, Benjamin Recht
2016	J	`jnl`	Gradient Descent Converges to Minimizers. CoRR Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht
2016	A*	`conf`	Gradient Descent Only Converges to Minimizers. COLT Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht
2016	A*	`conf`	Low-rank Solutions of Linear Matrix Equations via Procrustes Flow. ICML Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht