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09/26/2022
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency
The problem of estimating a linear functional based on observational dat...
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01/21/2022
Optimal variance-reduced stochastic approximation in Banach spaces
We study the problem of estimating the fixed point of a contractive oper...
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12/23/2021
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation
We study stochastic approximation procedures for approximately solving a...
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12/09/2020
Optimal oracle inequalities for solving projected fixed-point equations
Linear fixed point equations in Hilbert spaces arise in a variety of set...
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08/28/2020
ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm
The theory and practice of stochastic optimization has focused on stocha...
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08/17/2020
On the Sample Complexity of Reinforcement Learning with Policy Space Generalization
We study the optimal sample complexity in large-scale Reinforcement Lear...
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04/09/2020
On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration
We undertake a precise study of the asymptotic and non-asymptotic proper...
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12/11/2019
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing
We study the problem of sampling from the power posterior distribution i...
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10/01/2019
An Efficient Sampling Algorithm for Non-smooth Composite Potentials
We consider the problem of sampling from a density of the form p(x) ∝(-f...
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09/03/2019
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters
We show that diffusion processes can be exploited to study the posterior...
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08/28/2019
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm
We propose a Markov chain Monte Carlo (MCMC) algorithm based on third-or...
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07/25/2019
Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity
We present an improved analysis of the Euler-Maruyama discretization of ...
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07/19/2017
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints
Algorithm-dependent generalization error bounds are central to statistic...
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03/29/2017
Efficient Private ERM for Smooth Objectives
In this paper, we consider efficient differentially private empirical ri...
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12/14/2016