Max Simchowitz

Aleksandrs Slivkins

Oper. Res., 2024

Faster Algorithms for Growing Collision-Free Convex Polytopes in Robot Configuration Space.

[BibT_eX]

[DOI]

CoRR, 2024

Diffusion Policy Policy Optimization.

[BibT_eX]

[DOI]

CoRR, 2024

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion.

[BibT_eX]

[DOI]

CoRR, 2024

Constrained Bimanual Planning with Analytic Inverse Kinematics.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Robot Fleet Learning via Policy Merging.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use.

[BibT_eX]

[DOI]

CoRR, 2023

Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior.

[BibT_eX]

[DOI]

Daniel Pfrommer

CoRR, 2023

Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Smoothed Online Learning for Prediction in Piecewise Affine Systems.

[BibT_eX]

[DOI]

Russ Tedrake

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Statistical Learning under Heterogenous Distribution Shift.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Learning to Extrapolate: A Transductive Approach.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective.

[BibT_eX]

[DOI]

Abhishek Gupta

Kaiqing Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making.

[BibT_eX]

[DOI]

Alexander Rakhlin

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Globally Convergent Policy Search over Dynamic Filters for Output Estimation.

[BibT_eX]

[DOI]

CoRR, 2022

Do Differentiable Simulators Give Better Policy Gradients?

[BibT_eX]

[DOI]

CoRR, 2022

Globally Convergent Policy Search for Output Estimation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Do Differentiable Simulators Give Better Policy Gradients?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Beyond No Regret: Instance-Dependent PAC Reinforcement Learning.

[BibT_eX]

[DOI]

Andrew J. Wagenmaker

Kevin Jamieson

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Statistical Complexity and Regret in Linear Control.

[BibT_eX]

[DOI]

PhD thesis, 2021

A Successive-Elimination Approach to Adaptive Robotic Source Seeking.

[BibT_eX]

[DOI]

IEEE Trans. Robotics, 2021

Bayesian decision-making under misspecified priors with applications to meta-learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stabilizing Dynamical Systems via Policy Gradient Methods.

[BibT_eX]

[DOI]

Juan C. Perdomo

Jack Umenberger

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Control of Unknown Time-Varying Dynamical Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Task-Optimal Exploration in Linear Dynamical Systems.

[BibT_eX]

[DOI]

Andrew J. Wagenmaker

Proceedings of the 38th International Conference on Machine Learning, 2021

Towards a Dimension-Free Understanding of Adaptive Linear Control.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2021

Corruption-robust exploration in episodic reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2021

On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Making Non-Stochastic Control (Almost) as Easy as Stochastic.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning the Linear Quadratic Regulator from Nonlinear Observations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Constrained episodic reinforcement learning in concave-convex and knapsack settings.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Naive Exploration is Optimal for Online LQR.

[BibT_eX]

[DOI]

Dylan J. Foster

Proceedings of the 37th International Conference on Machine Learning, 2020

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Reward-Free Exploration for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Logarithmic Regret for Adversarial Online Control.

[BibT_eX]

[DOI]

Dylan J. Foster

Proceedings of the 37th International Conference on Machine Learning, 2020

Improper Learning for Non-Stochastic Control.

[BibT_eX]

[DOI]

Karan Singh

Elad Hazan

Proceedings of the Conference on Learning Theory, 2020

The Gradient Complexity of Linear Regression.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2020

2019

First-order methods almost always avoid strict saddle points.

[BibT_eX]

[DOI]

Math. Program., 2019

Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The Implicit Fairness Criterion of Unconstrained Learning.

[BibT_eX]

[DOI]

Lydia T. Liu

Moritz Hardt

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Linear Dynamical Systems with Semi-Parametric Least Squares.

[BibT_eX]

[DOI]

Ross Boczar

Proceedings of the Conference on Learning Theory, 2019

2018

A Successive-Elimination Approach to Adaptive Robotic Sensing.

[BibT_eX]

[DOI]

CoRR, 2018

Group calibration is a byproduct of unconstrained learning.

[BibT_eX]

[DOI]

Lydia T. Liu

Moritz Hardt

CoRR, 2018

Adaptive Sampling for Convex Regression.

[BibT_eX]

[DOI]

CoRR, 2018

On the Randomized Complexity of Minimizing a Convex Quadratic Function.

[BibT_eX]

[DOI]

CoRR, 2018

Tight query complexity lower bounds for PCA via finite sample deformed wigner law.

[BibT_eX]

[DOI]

Ahmed El Alaoui

Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018

Delayed Impact of Fair Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

Approximate ranking from pairwise comparisons.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

First-order Methods Almost Always Avoid Saddle Points.

[BibT_eX]

[DOI]

CoRR, 2017

On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation.

[BibT_eX]

[DOI]

Ahmed El Alaoui

CoRR, 2017

The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime.

[BibT_eX]

[DOI]

Proceedings of the 30th Conference on Learning Theory, 2017

2016

Gradient Descent Converges to Minimizers.

[BibT_eX]

[DOI]

CoRR, 2016

Low-rank Solutions of Linear Matrix Equations via Procrustes Flow.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Best-of-K-bandits.

[BibT_eX]

[DOI]