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09/15/2023
Constrained Bimanual Planning with Analytic Inverse Kinematics
In order for a bimanual robot to manipulate an object that is held by bo...
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08/31/2023
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
Visual model-based RL methods typically encode image observations into l...
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07/27/2023
Imitating Complex Trajectories: Bridging Low-Level Stability and High-Level Behavior
We propose a theoretical framework for studying the imitation of stochas...
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07/12/2023
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective
Obtaining rigorous statistical guarantees for generalization under distr...
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05/16/2023
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
A common pipeline in learning-based control is to iteratively estimate a...
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05/10/2023
Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets
Computing optimal, collision-free trajectories for high-dimensional syst...
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04/27/2023
Learning to Extrapolate: A Transductive Approach
Machine learning systems, especially with overparameterized deep neural ...
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02/27/2023
Statistical Learning under Heterogenous Distribution Shift
This paper studies the prediction of a target 𝐳 from a pair of random va...
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02/10/2023
Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making
Smoothed online learning has emerged as a popular framework to mitigate ...
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01/26/2023
Smoothed Online Learning for Prediction in Piecewise Affine Systems
The problem of piecewise affine (PWA) regression and planning is of foun...
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05/25/2022
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions
Due to the drastic gap in complexity between sequential and batch statis...
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02/23/2022
Globally Convergent Policy Search over Dynamic Filters for Output Estimation
We introduce the first direct policy search algorithm which provably con...
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02/16/2022
Online Control of Unknown Time-Varying Dynamical Systems
We study online control of time-varying linear systems with unknown dyna...
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02/02/2022
Do Differentiable Simulators Give Better Policy Gradients?
Differentiable simulators promise faster computation time for reinforcem...
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01/26/2022
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes
Reward-free reinforcement learning (RL) considers the setting where the ...
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12/07/2021
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
Obtaining first-order regret bounds – regret bounds scaling not as the w...
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10/13/2021
Stabilizing Dynamical Systems via Policy Gradient Methods
Stabilizing an unknown control system is one of the most fundamental pro...
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08/05/2021
Beyond No Regret: Instance-Dependent PAC Reinforcement Learning
The theory of reinforcement learning has focused on two fundamental prob...
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07/03/2021
Bayesian decision-making under misspecified priors with applications to meta-learning
Thompson sampling and other Bayesian sequential decision-making algorith...
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03/27/2021
On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
The widespread adoption of nonlinear Receding Horizon Control (RHC) stra...
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03/19/2021
Towards a Dimension-Free Understanding of Adaptive Linear Control
We study the problem of adaptive control of the linear quadratic regulat...
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02/28/2021
Exploration and Incentives in Reinforcement Learning
How do you incentivize self-interested agents to explore when they prefe...
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02/10/2021
Task-Optimal Exploration in Linear Dynamical Systems
Exploration in unknown environments is a fundamental problem in reinforc...
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10/08/2020
Learning the Linear Quadratic Regulator from Nonlinear Observations
We introduce a new problem setting for continuous control called the LQR...
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06/10/2020
Making Non-Stochastic Control (Almost) as Easy as Stochastic
Recent literature has made much progress in understanding online LQR: a ...
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06/09/2020
Constrained episodic reinforcement learning in concave-convex and knapsack settings
We propose an algorithm for tabular episodic reinforcement learning with...
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03/15/2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning
While real-world decisions involve many competing objectives, algorithmi...
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02/29/2020
Logarithmic Regret for Adversarial Online Control
We introduce a new algorithm for online linear-quadratic control in a kn...
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02/07/2020
Reward-Free Exploration for Reinforcement Learning
Exploration is widely regarded as one of the most challenging aspects of...
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01/27/2020
Naive Exploration is Optimal for Online LQR
We consider the problem of online adaptive control of the linear quadrat...
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01/25/2020
Improper Learning for Non-Stochastic Control
We consider the problem of controlling a possibly unknown linear dynamic...
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11/20/2019
Corruption Robust Exploration in Episodic Reinforcement Learning
We initiate the study of multi-stage episodic reinforcement learning und...
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11/06/2019
The gradient complexity of linear regression
We investigate the computational complexity of several basic linear alge...
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05/09/2019
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs
This paper establishes that optimistic algorithms attain gap-dependent a...
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02/02/2019
Learning Linear Dynamical Systems with Semi-Parametric Least Squares
We analyze a simple prefiltered variation of the least squares estimator...
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09/27/2018
A Successive-Elimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
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08/29/2018
Group calibration is a byproduct of unconstrained learning
Much recent work on fairness in machine learning has focused on how well...
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08/14/2018
Adaptive Sampling for Convex Regression
In this paper, we introduce the first principled adaptive-sampling proce...
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07/24/2018
On the Randomized Complexity of Minimizing a Convex Quadratic Function
Minimizing a convex, quadratic objective is a fundamental problem in mac...
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04/04/2018
Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law
We prove a query complexity lower bound for approximating the top r dime...
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03/12/2018
Delayed Impact of Fair Machine Learning
Fairness in machine learning has predominantly been studied in static cl...
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02/22/2018
Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
We prove that the ordinary least-squares (OLS) estimator attains nearly ...
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01/04/2018
Approximate Ranking from Pairwise Comparisons
A common problem in machine learning is to rank a set of n items based o...
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10/20/2017
First-order Methods Almost Always Avoid Saddle Points
We establish that first-order methods avoid saddle points for almost all...
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04/14/2017
On the Gap Between Strict-Saddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation
We prove a query complexity lower bound on rank-one principal component ...
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02/16/2017
The Simulator: Understanding Adaptive Sampling in the Moderate-Confidence Regime
We propose a novel technique for analyzing adaptive sampling called the ...
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03/09/2016
Best-of-K Bandits
This paper studies the Best-of-K Bandit game: At each time the player ch...
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02/16/2016