Xingyu

Xingyu Zhou

xingyu (dot) zhou (at) wayne (dot) edu


About

I am currently an Assistant Professor in the Department of Electrical and Computer Engineering of Wayne State University. I received my Ph.D. in ECE at Ohio State University, advised by Prof. Ness Shroff. Prior to that, I graduated from BUPT with
a B.S. and Tsinghua University with an M.S., both in Electrical Engineering.

I have also been a machine learing engineer intern at Facebook and a research intern at Alibaba, USA advised by Jian Tan.


Research Overview

My research interests include both machine learning and stochastic systems. On the learning side, I mainly focus on bandits and reinforcement learning with a focus on differential privacy. On the stochastic systems side, I primarily work on load balancing problems with applications in data centers and cloud computing.


Selected Preprints

(* denotes equal contributions)


Multi-Armed Bandits with Local Differential Privacy
Wenbo Ren, Xingyu Zhou, Jia Liu and Ness Shroff
Arxiv

On the Fenchel Duality between Strong Convexity and Lipschitz Continuous Gradient
Xingyu Zhou
Arxiv, [blog post]

A Note on Stein’s Method for Heavy-Traffic Analysis
Xingyu Zhou and Ness Shroff
Arxiv


Recent Publications

(* denotes equal contributions)


Locally Private and Robust Multi-Armed Bandits
Xingyu Zhou, Wei Zhang
NeurIPS 2024
Short version accepted by TPDP'24

Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting
Duo Cheng, Xingyu Zhou, Bo Ji
NeurIPS 2024

Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
(α-β order) Changyu Gao*, Andrew Lowy*, Xingyu Zhou*, Stephen Wright
ICML 2024

On Differentially Private Federated Linear Contextual Bandits
Xingyu Zhou and Sayak Ray Chowdhury
ICLR 2024
Short version accepted by FL Workshop @ ICML 2023 and TPDP'23

Differentially Private Reward Estimation with Preference Feedback
Sayak Ray Chowdhury*, Xingyu Zhou*, Nagarajan Natarajan
AISTATS 2024

Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL
Arnob Ghosh, Xingyu Zhou, Ness Shroff
AISTATS 2024

On Private and Robust Bandits
Yulian Wu*, Xingyu Zhou*, Youming Tao, Di Wang
NeurIPS 2023

More Publications

Understanding the Role of Feedback in Online Learning with Switching Costs
Duo Cheng, Xingyu Zhou, Bo Ji
ICML 2023

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang
ICML 2023

Distributed Differential Privacy in Multi-Armed Bandits
Sayak Ray Chowdhury*, Xingyu Zhou*
ICLR 2023, [slides]
Short version accepted by Trustworthy and Socially Responsible ML (TSRML) at NeurIPS 2022

Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation
Arnob Ghosh, Xingyu Zhou, Ness Shroff
ICLR 2023

(Private) Kernelized Bandits with Distributed Biased Feedback
Fengjiao Li, Xingyu Zhou, Bo Ji
ACM Sigmetrics 2023 (acceptance rate ~ 21.8%), [slides]

On Kernelized Multi-Armed Bandits with Constraints
Xingyu Zhou, Bo Ji
NeurIPS 2022 (acceptance rate ~ 25.6%), [slides]

Provably Efficient Model-Free Constrained RL with Linear Function Approximation
Arnob Ghosh, Xingyu Zhou, Ness Shroff
NeurIPS 2022 (acceptance rate ~ 25.6%)

Differentially Private Linear Bandits with Partial Distributed Feedback
Fengjiao Li, Xingyu Zhou, Bo Ji
WiOpt 2022 (Best Student Paper)

Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits
Yuntian Deng, Xingyu Zhou, Arnob Ghosh, Abhishek Gupta, Ness Shroff
WiOpt 2022 (Best Student Paper Runner-Up)

Shuffle Private Linear Contextual Bandits
Sayak Ray Chowdhury*, Xingyu Zhou*
ICML 2022 (acceptance rate ~ 22%), [slides]

Weighted Gaussian Process Bandits for Non-stationary Environments
Yuntian Deng, Xingyu Zhou, Baekjin Kim, Ambuj Tewari, Abhishek Gupta, Ness Shroff
AISTATS 2022 (acceptance rate ~ 28%)

Differentially Private Reinforcement Learning with Linear Function Approximation
Xingyu Zhou
ACM Sigmetrics/IFIP Performance 2022 (acceptance rate ~ 20%)

Differentially Private Regret Minimization in Episodic Markov Decision Processes
Sayak Ray Chowdhury*, Xingyu Zhou*
AAAI 2022, Oral Presentation (oral acceptance rate ~ 4.6%)

Adaptive Control of Differentially Private Linear Quadratic Systems
Sayak Ray Chowdhury*, Xingyu Zhou* and Ness Shroff
ISIT 2021

Local Differential Privacy for Bayesian Optimization
Xingyu Zhou and Jian Tan
AAAI 2021 (acceptance rate ~ 21%)

No-Regret Algorithms for Time-Varying Bayesian Optimization
Xingyu Zhou and Ness Shroff
CISS 2021 (invited)

Optimal Load Balancing with Locality Constraints
Wentao Weng, Xingyu Zhou, and R. Srikant
ACM Sigmetrics 2021 (acceptance rate ~ 12%)

Asymptotically Optimal Load Balancing in Large-scale Heterogeneous Systems with Multiple Dispatchers
Xingyu Zhou, Ness Shroff and Adam Wierman
IFIP Performance 2020

Heavy-traffic Delay Optimality in Pull-based Load Balancing Systems: Necessary and Sufficient Conditions
Xingyu Zhou, Jian Tan and Ness Shroff
ACM Sigmetrics/IFIP Performance 2019 (acceptance rate ~ 16%)

Flexible Load Balancing with Multi-dimensional State-space Collapse: Throughput and Heavy-traffic Delay Optimality
Xingyu Zhou, Jian Tan and Ness Shroff
IFIP Performance 2018

Degree of Queue Imbalance: Overcoming the Limitation of Heavy-traffic Delay Optimality in Load Balancing Systems
Xingyu Zhou*, Fei Wu*, Jian Tan, Kannan Srinivasan, and Ness Shroff
ACM Sigmetrics 2018 (acceptance rate ~ 20%)

Designing Low-Complexity Heavy-Traffic Delay-Optimal Load Balancing Schemes: Theory to Algorithms
Xingyu Zhou, Fei Wu, Jian Tan, Yin Sun, Ness Shroff
ACM Sigmetrics 2018 (acceptance rate ~ 20%)


Teaching

ECE 7995: Online Decision Making, Wayne State University, Fall-2021.

ECE 4050/CSC 5050: Algorithms and Data Structures, Wayne State University, Winter-2021,2022, Fall-2022.

ECE 2050: Object-Oriented Programming for ECE, Wayne State University, Fall-2022, 2023.


Invited Talks

On Differentially Private Federated Linear Contextual Bandits
AI-EDGE Seminar (hosted by Prof. Ness Shroff), Mar. 2023 pdf
Robotics and Control Seminar (hosted by Prof. Vaibhav Srivastava), Sep. 2023 pdf

Shuffle Private Linear Contextual Bandits pdf
UCLA Big Data and Machine Learning Seminar (hosted by Prof. Quanquan Gu), Jun. 2022

Stein’s Method for Heavy-traffic Analysis: Load Balancing and Scheduling pdf
YEQT workshop, Virtual, Jun. 2021

Stein’s Method for Heavy-traffic Analysis With Applications in Load Balancing And Scheduling pdf
INFORMS Annual Meeting, Virtual, Oct. 2021

Asymptotically Optimal Load Balancing in Large-scale Heterogeneous Systems with Multiple Dispatchers pdf
INFORMS Annual Meeting, Virtual, Oct. 2020

Heavy-traffic Delay Optimality in Pull-based Load Balancing Systems: Necessary and Sufficient Conditions
INFORMS Annual Meeting, Seattle, Oct. 2019

Heavy-traffic Delay Optimality in Pull-based Load Balancing Systems: Necessary and Sufficient Conditions pdf
RSRG Seminar (hosted by Prof. Adam Wierman), Caltech, Feb. 2019

Load balancing in heavy traffic: Theory and algorithms
SQUALL seminar (hosted by Prof. Mor Harchol-Balter), CMU, Sep. 2018


Award

Best Student Paper Award, WiOpt 2022

Best Student Paper Runner-Up, WiOpt 2022

NSF CISE Research Initiation Initiative Award

Presidential Fellowship, The Ohio State University 2019 (the highest honor at OSU).

Student Travel Grant, ACM Sigmetrics 2018, 2019

Student Travel Grant, IFIP Performance 2018.

Excellent Dissertation Award, Chinese Institute of Electronics, 2016

Outstanding Graduate Award of Beijing city, 2012 and 2015.

Outstanding Graduate Award, BUPT and Tsinghua University, 2012 and 2015.

Distinguished Dissertation Award, BUPT and Tsinghua University, 2012 and 2015.

Academic Rising Star Award, Electrical Engineering, Tsinghua University, 2015.

“The December 9th” Scholarship, Tsinghua University, 2014.

National Scholarship, Ministry of Education, China, 2011 and 2014.

HNA (HaiNan Airlines) Academic Excellence Scholarship, 2011.

First prize in National Undergraduate Electronic Design Contest, 2011.

First prize in National “Freescale Cup” Intelligent Car Competition, 2011.


Others

This is my previous CSDN blog in Chinese and it will not be updated. A new blog has been created recently.

My inspirations of research and life come from two Claudes: Claude Shannon and Claude Monet