
On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
The widespread adoption of nonlinear Receding Horizon Control (RHC) stra...
read it

Towards a DimensionFree Understanding of Adaptive Linear Control
We study the problem of adaptive control of the linear quadratic regulat...
read it

Exploration and Incentives in Reinforcement Learning
How do you incentivize selfinterested agents to explore when they prefe...
read it

TaskOptimal Exploration in Linear Dynamical Systems
Exploration in unknown environments is a fundamental problem in reinforc...
read it

Learning the Linear Quadratic Regulator from Nonlinear Observations
We introduce a new problem setting for continuous control called the LQR...
read it

Making NonStochastic Control (Almost) as Easy as Stochastic
Recent literature has made much progress in understanding online LQR: a ...
read it

Constrained episodic reinforcement learning in concaveconvex and knapsack settings
We propose an algorithm for tabular episodic reinforcement learning with...
read it

Balancing Competing Objectives with Noisy Data: ScoreBased Classifiers for WelfareAware Machine Learning
While realworld decisions involve many competing objectives, algorithmi...
read it

Logarithmic Regret for Adversarial Online Control
We introduce a new algorithm for online linearquadratic control in a kn...
read it

RewardFree Exploration for Reinforcement Learning
Exploration is widely regarded as one of the most challenging aspects of...
read it

Naive Exploration is Optimal for Online LQR
We consider the problem of online adaptive control of the linear quadrat...
read it

Improper Learning for NonStochastic Control
We consider the problem of controlling a possibly unknown linear dynamic...
read it

Corruption Robust Exploration in Episodic Reinforcement Learning
We initiate the study of multistage episodic reinforcement learning und...
read it

The gradient complexity of linear regression
We investigate the computational complexity of several basic linear alge...
read it

NonAsymptotic GapDependent Regret Bounds for Tabular MDPs
This paper establishes that optimistic algorithms attain gapdependent a...
read it

Learning Linear Dynamical Systems with SemiParametric Least Squares
We analyze a simple prefiltered variation of the least squares estimator...
read it

A SuccessiveElimination Approach to Adaptive Robotic Sensing
We study the adaptive sensing problem for the multiple source seeking pr...
read it

Group calibration is a byproduct of unconstrained learning
Much recent work on fairness in machine learning has focused on how well...
read it

Adaptive Sampling for Convex Regression
In this paper, we introduce the first principled adaptivesampling proce...
read it

On the Randomized Complexity of Minimizing a Convex Quadratic Function
Minimizing a convex, quadratic objective is a fundamental problem in mac...
read it

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...
read it

Delayed Impact of Fair Machine Learning
Fairness in machine learning has predominantly been studied in static cl...
read it

Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification
We prove that the ordinary leastsquares (OLS) estimator attains nearly ...
read it

Approximate Ranking from Pairwise Comparisons
A common problem in machine learning is to rank a set of n items based o...
read it

Firstorder Methods Almost Always Avoid Saddle Points
We establish that firstorder methods avoid saddle points for almost all...
read it

On the Gap Between StrictSaddles and True Convexity: An Omega(log d) Lower Bound for Eigenvector Approximation
We prove a query complexity lower bound on rankone principal component ...
read it

The Simulator: Understanding Adaptive Sampling in the ModerateConfidence Regime
We propose a novel technique for analyzing adaptive sampling called the ...
read it

BestofK Bandits
This paper studies the BestofK Bandit game: At each time the player ch...
read it

Gradient Descent Converges to Minimizers
We show that gradient descent converges to a local minimizer, almost sur...
read it
Max Simchowitz
is this you? claim profile