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06/24/2022
Joint Representation Training in Sequential Tasks with Shared Structure
Classical theory in reinforcement learning (RL) predominantly focuses on...
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06/16/2022
Generalization Bounds for Data-Driven Numerical Linear Algebra
Data-driven algorithms can adapt their internal structure or parameters ...
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03/08/2022
A Sharp Characterization of Linear Estimators for Offline Policy Evaluation
Offline policy evaluation is a fundamental statistical problem in reinfo...
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11/08/2021
An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed Bandit
We study the problem of information sharing and cooperation in Multi-Pla...
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05/21/2021
Parallelizing Contextual Linear Bandits
Standard approaches to decision-making under uncertainty focus on sequen...
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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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03/17/2021
Near Optimal Policy Optimization via REPS
Since its introduction a decade ago, relative entropy policy search (REP...
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12/24/2020
Regret Bound Balancing and Elimination for Model Selection in Bandits and RL
We propose a simple model selection approach for algorithms in stochasti...
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07/01/2020
Accelerated Message Passing for Entropy-Regularized MAP Inference
Maximum a posteriori (MAP) inference in discrete-valued Markov random fi...
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06/17/2020
Stochastic Bandits with Linear Constraints
We study a constrained contextual linear bandit setting, where the goal ...
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03/06/2020
Dropout: Explicit Forms and Capacity Control
We investigate the capacity control provided by dropout in various machi...
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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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02/04/2019
Is There an Analog of Nesterov Acceleration for MCMC?
We formulate gradient-based Markov chain Monte Carlo (MCMC) sampling as ...
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10/29/2018
Rademacher Complexity for Adversarially Robust Generalization
Many machine learning models are vulnerable to adversarial attacks. It h...
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06/14/2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
In this paper, we study robust large-scale distributed learning in the p...
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03/05/2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
In large-scale distributed learning, security issues have become increas...
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06/26/2017
Spectrally-normalized margin bounds for neural networks
This paper presents a margin-based multiclass generalization bound for n...
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05/25/2017
Convergence of Langevin MCMC in KL-divergence
Langevin diffusion is a commonly used tool for sampling from a given dis...
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05/19/2013
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
We study online learning under logarithmic loss with regular parametric ...
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04/12/2013
Advice-Efficient Prediction with Expert Advice
Advice-efficient prediction with expert advice (in analogy to label-effi...
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04/05/2011