Zhihan Xiong

I am a second-year PhD student in the Paul G. Allen School of Computer Science & Engineering at University of Washington, advised by Prof. Maryam Fazel.

My research interest lies in a convex combination of machine learning, statistics and optimization.

Prior to UW, I received my Master's Degree in Statistics from Stanford University in 2020 and Bachelor's Degree in Mathematics and Engineering Physics from University of Illinois at Urbana-Champaign in 2018, where I was fortunate to be advised by Prof. Pierre Moulin.

Email  /  CV  /  LinkedIn

Publications/ Preprints

Learning in Congestion Games with Bandit Feedback [arXiv]
Qiwen Cui*, Zhihan Xiong*, Maryam Fazel, Simon S. Du

Near-Optimal Randomized Exploration for Tabular Markov Decision Processes [arXiv]
Zhihan Xiong*, Ruoqi Shen*, Qiwen Cui*, Maryam Fazel, Simon S. Du

Fourier Learning with Cyclical Data
Yingxiang Yang*, Zhihan Xiong*, Tianyi Liu*, Taiqing Wang, Chong Wang
International Conference on Machine Learning (ICML), 2022

Selective Sampling for Online Best-arm Identification [arXiv]
Romain Camilleri* , Zhihan Xiong*, Maryam Fazel, Lalit Jain, Kevin Jamieson
Neural Information Processing Systems (NeurIPS), 2021

Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning [arXiv]
Tian Tan*, Zhihan Xiong*, Vikranth R. Dwaracherla
Association for the Advancement of Artificial Intelligence (AAAI, Oral), 2020

Project Reports

Few-Shot Learning on Google Landmark Challenge [pdf]
Zhihan Xiong, Mi Jeremy Yu, Louise Qianying Huang
CS 231N: Convolutional Neural Networks for Visual Recognition, Stanford University

Adversarial Machine Learning with GAN [pdf]
Zhihan Xiong, Pierre Moulin
Undergraduate Senior Thesis

Teaching and Professional Service

CS 229: Machine Learning, Teaching Assistant, Autumn 2019, Spring 2020 Stanford University, CA
CS 234: Reinforcement Learning, Teaching Assistant, Winter 2020 Stanford University, CA

Reviewer for: ICML (2021, 2022), NeurIPS (2021, 2022), ICLR (2022).