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Featured Co-authors

Jie Zhou
349 publications
Jian Yang
171 publications
Yang Yu
155 publications
Csaba Szepesvari
116 publications
Mengdi Wang
91 publications
Dale Schuurmans
78 publications
Xin Zhou
74 publications
Guang Cheng
70 publications
Benjamin Van Roy
63 publications
Tor Lattimore
57 publications
Guang Lin
56 publications

∙ 05/17/2023

Sequential Best-Arm Identification with Application to Brain-Computer Interface

A brain-computer interface (BCI) is a technology that enables direct com...

0 Xin Zhou, et al. ∙

∙ 03/20/2023

Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale

In this paper, we address the following problem: Given an offline demons...

0 Botao Hao, et al. ∙

∙ 02/07/2023

Leveraging Demonstrations to Improve Online Learning: Quality Matters

We investigate the extent to which offline demonstration data can improv...

0 Botao Hao, et al. ∙

∙ 01/29/2023

Sample Efficient Deep Reinforcement Learning via Local Planning

The focus of this work is sample-efficient deep reinforcement learning (...

0 Dong Yin, et al. ∙

∙ 06/09/2022

Regret Bounds for Information-Directed Reinforcement Learning

Information-directed sampling (IDS) has revealed its potential as a data...

0 Botao Hao, et al. ∙

∙ 05/22/2022

Contextual Information-Directed Sampling

Information-directed sampling (IDS) has recently demonstrated its potent...

0 Botao Hao, et al. ∙

∙ 02/20/2022

Interacting Contour Stochastic Gradient Langevin Dynamics

We propose an interacting contour stochastic gradient Langevin dynamics ...

0 Wei Deng, et al. ∙

∙ 10/09/2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

Posterior predictive distributions quantify uncertainties ignored by poi...

0 Ian Osband, et al. ∙

∙ 08/12/2021

Efficient Local Planning with Linear Function Approximation

We study query and computationally efficient planning algorithms with li...

0 Dong Yin, et al. ∙

∙ 06/03/2021

Bandit Phase Retrieval

We study a bandit version of phase retrieval where the learner chooses a...

0 Tor Lattimore, et al. ∙

∙ 05/29/2021

Information Directed Sampling for Sparse Linear Bandits

Stochastic sparse linear bandits offer a practical model for high-dimens...

0 Botao Hao, et al. ∙

∙ 02/11/2021

Optimization Issues in KL-Constrained Approximate Policy Iteration

Many reinforcement learning algorithms can be seen as versions of approx...

0 Nevena Lazic, et al. ∙

∙ 02/06/2021

Bootstrapping Statistical Inference for Off-Policy Evaluation

Bootstrapping provides a flexible and effective approach for assessing t...

0 Botao Hao, et al. ∙

∙ 11/08/2020

High-Dimensional Sparse Linear Bandits

Stochastic linear bandits with high-dimensional sparse features are a pr...

0 Botao Hao, et al. ∙

∙ 11/08/2020

Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient

This paper provides a statistical analysis of high-dimensional batch Rei...

0 Botao Hao, et al. ∙

∙ 11/08/2020

Online Sparse Reinforcement Learning

We investigate the hardness of online reinforcement learning in fixed ho...

0 Botao Hao, et al. ∙

∙ 07/31/2020

Low-rank Tensor Bandits

In recent years, multi-dimensional online decision making has been playi...

4 Botao Hao, et al. ∙

∙ 02/19/2020

Residual Bootstrap Exploration for Bandit Algorithms

In this paper, we propose a novel perturbation-based exploration method ...

0 Chi-Hua Wang, et al. ∙

∙ 02/08/2020

Provably Efficient Adaptive Approximate Policy Iteration

Model-free reinforcement learning algorithms combined with value functio...

15 Botao Hao, et al. ∙

∙ 10/15/2019

Adaptive Exploration in Linear Contextual Bandit

Contextual bandits serve as a fundamental model for many sequential deci...

0 Botao Hao, et al. ∙

∙ 06/12/2019

Bootstrapping Upper Confidence Bound

Upper Confidence Bound (UCB) method is arguably the most celebrated one ...

0 Botao Hao, et al. ∙

∙ 03/31/2019

Sparse Tensor Additive Regression

Tensors are becoming prevalent in modern applications such as medical im...

0 Botao Hao, et al. ∙

∙ 01/29/2018

Sparse and Low-rank Tensor Estimation via Cubic Sketchings

In this paper, we propose a general framework for sparse and low-rank te...

0 Botao Hao, et al. ∙

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