research
∙
07/14/2023
Adaptive Linear Estimating Equations
Sequential data collection has emerged as a widely adopted technique for...
share
research
∙
03/05/2023
Semi-parametric inference based on adaptively collected data
Many standard estimators, when applied to adaptively collected data, fai...
research
∙
01/21/2022
Instance-Dependent Confidence and Early Stopping for Reinforcement Learning
Various algorithms for reinforcement learning (RL) exhibit dramatic vari...
research
∙
01/21/2022
Optimal variance-reduced stochastic approximation in Banach spaces
We study the problem of estimating the fixed point of a contractive oper...
research
∙
07/05/2021
Near-optimal inference in adaptive linear regression
When data is collected in an adaptive manner, even simple methods like o...
research
∙
06/28/2021
Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning
Various algorithms in reinforcement learning exhibit dramatic variabilit...
research
∙
05/22/2020
Instability, Computational Efficiency and Statistical Accuracy
Many statistical estimators are defined as the fixed point of a data-dep...
research
∙
03/16/2020
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis
We address the problem of policy evaluation in discounted Markov decisio...
research
∙
02/01/2019
Challenges with EM in application to weakly identifiable mixture models
We study a class of weakly identifiable location-scale mixture models fo...
research
∙
12/20/2018
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
We study derivative-free methods for policy optimization over the class ...
research
∙
10/01/2018
Singularity, Misspecification, and the Convergence Rate of EM
A line of recent work has characterized the behavior of the EM algorithm...
research
∙
04/25/2018
Convergence guarantees for a class of non-convex and non-smooth optimization problems
We consider the problem of finding critical points of functions that are...
research
∙
01/18/2018