b'Shaofeng Zou'

research

∙ 07/30/2023

Robust Multi-Agent Reinforcement Learning with State Uncertainty

In real-world multi-agent reinforcement learning (MARL) applications, ag...

0 Sihong He, et al. ∙

research

∙ 05/22/2023

Distributionally Robust Optimization Efficiently Solves Offline Reinforcement Learning

Offline reinforcement learning aims to find the optimal policy from a pr...

0 Yue Wang, et al. ∙

research

∙ 05/17/2023

Model-Free Robust Average-Reward Reinforcement Learning

Robust Markov decision processes (MDPs) address the challenge of model u...

0 Yue Wang, et al. ∙

research

∙ 01/02/2023

Robust Average-Reward Markov Decision Processes

In robust Markov decision processes (MDPs), the uncertainty in the trans...

0 Yue Wang, et al. ∙

research

∙ 10/23/2022

Robust Hypothesis Testing with Moment Constrained Uncertainty Sets

The problem of robust binary hypothesis testing is studied. Under both h...

0 Akshayaa Magesh, et al. ∙

research

∙ 09/21/2022

Understanding Information Disclosure from Secure Computation Output: A Study of Average Salary Computation

Secure multi-party computation have seen substantial performance improve...

0 Alessandro Baccarini, et al. ∙

research

∙ 09/17/2022

A Robust and Constrained Multi-Agent Reinforcement Learning Framework for Electric Vehicle AMoD Systems

Electric vehicles (EVs) play critical roles in autonomous mobility-on-de...

10 Sihong He, et al. ∙

research

∙ 09/14/2022

Robust Constrained Reinforcement Learning

Constrained reinforcement learning is to maximize the expected reward su...

18 Yue Wang, et al. ∙

research

∙ 05/15/2022

Policy Gradient Method For Robust Reinforcement Learning

This paper develops the first policy gradient method with global optimal...

3 Yue Wang, et al. ∙

research

∙ 03/23/2022

Kernel Robust Hypothesis Testing

The problem of robust hypothesis testing is studied, where under the nul...

0 Zhongchang Sun, et al. ∙

research

∙ 10/20/2021

Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process

The problem of constrained Markov decision process (CMDP) is investigate...

0 Tianjiao Li, et al. ∙

research

∙ 09/29/2021

Online Robust Reinforcement Learning with Model Uncertainty

Robust reinforcement learning (RL) is to find a policy that optimizes th...

0 Yue Wang, et al. ∙

research

∙ 09/08/2021

Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis

Actor-critic (AC) algorithms have been widely adopted in decentralized m...

0 Ziyi Chen, et al. ∙

research

∙ 04/09/2021

Sequential (Quickest) Change Detection: Classical Results and New Directions

Online detection of changes in stochastic systems, referred to as sequen...

0 Liyan Xie, et al. ∙

research

∙ 04/07/2021

Finite-Sample Analysis for Two Time-scale Non-linear TDC with General Smooth Function Approximation

Temporal-difference learning with gradient correction (TDC) is a two tim...

0 Yue Wang, et al. ∙

research

∙ 03/30/2021

Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity

Greedy-GQ is a value-based reinforcement learning (RL) algorithm for opt...

0 Shaocong Ma, et al. ∙

research

∙ 12/07/2020

Learning Graph Neural Networks with Approximate Gradient Descent

The first provably efficient algorithm for learning graph neural network...

0 Qunwei Li, et al. ∙

research

∙ 10/26/2020

Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis

Variance reduction techniques have been successfully applied to temporal...

2 Shaocong Ma, et al. ∙

research

∙ 05/20/2020

Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise

Greedy-GQ is an off-policy two timescale algorithm for optimal control i...

11 Yue Wang, et al. ∙

research

∙ 03/16/2020

A CNN-Based Blind Denoising Method for Endoscopic Images

The quality of images captured by wireless capsule endoscopy (WCE) is ke...

0 Shaofeng Zou, et al. ∙

research

∙ 09/26/2019

Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples

Gradient-based temporal difference (GTD) algorithms are widely used in o...

0 Tengyu Xu, et al. ∙

research

∙ 02/06/2019

Finite-Sample Analysis for SARSA and Q-Learning with Linear Function Approximation

Though the convergence of major reinforcement learning algorithms has be...

0 Shaofeng Zou, et al. ∙

research

∙ 01/27/2019

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

We show that model compression can improve the population risk of a pre-...

0 Yuheng Bu, et al. ∙

research

∙ 01/15/2019

Tightening Mutual Information Based Bounds on Generalization Error

A mutual information based upper bound on the generalization error of a ...

1 Yuheng Bu, et al. ∙

research

∙ 07/16/2018

Quickest Detection of Dynamic Events in Networks

The problem of quickest detection of dynamic events in networks is studi...

0 Shaofeng Zou, et al. ∙

research

∙ 11/06/2017

Quickest Change Detection under Transient Dynamics: Theory and Asymptotic Analysis

The problem of quickest change detection (QCD) under transient dynamics ...

0 Shaofeng Zou, et al. ∙

research

∙ 01/21/2017

Linear-Complexity Exponentially-Consistent Tests for Universal Outlying Sequence Detection

The problem of universal outlying sequence detection is studied, where t...

0 Yuheng Bu, et al. ∙

research

∙ 04/05/2016

Nonparametric Detection of Geometric Structures over Networks

Nonparametric detection of existence of an anomalous structure over a ne...

0 Shaofeng Zou, et al. ∙

research

∙ 04/25/2014

Nonparametric Detection of Anomalous Data Streams

A nonparametric anomalous hypothesis testing problem is investigated, in...

0 Shaofeng Zou, et al. ∙

research

∙ 04/01/2014

A Kernel-Based Nonparametric Test for Anomaly Detection over Line Networks

The nonparametric problem of detecting existence of an anomalous interva...

0 Shaofeng Zou, et al. ∙

Shaofeng Zou

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