About

Hello and welcome to my home page! Here I post my research background and other related experiences. My name is William Chang and in 2022 I graduated from University of Southern California with a B.A. in mathematics. Since 2023 Fall, I’ve been a PhD student at University of California, Los Angeles in Applied mathematics.

My research interests are rather diverse. It mainly span across mathematics and machine learning. Please see my papers below for more details on my work.

On the side I enjoy tutoring students. I’m willing to tutor students in math and physics at all levels (elementary, middle, high school, and university level as well). You can see my past students and book a session with me via my [Takelessons Profile].

In my free time I like to practice Taekwondo and sing. Please feel free to check out my cover channel on youtube [@WilliamChangMusic]! Please also follow me on [Spotify]!

Please feel free to reach out to me for anything via chang314@g.ucla.edu!

Multiplayer Bandits

  1. Multiplayer Lipschitz bandits with information asymmetry
    William Chang, Terry Lu

  2. LinUCB in Multiplayer Information Asymmetric Contextual Bandits
    William Chang, Terry Lu

  3. Optimal Cooperative Multiplayer Learning Bandits with Noisy Rewards and No Communication [PDF]
    William Chang, Terry Lu

  4. Finite-Time Regret Bound of Multi-Agent Thompson Sampling
    Tianyuan Jin, Haolun Hsu, William Chang, Pan Xu
    Association for the Advancement of Artificial Intelligence, 2024

  5. Online Learning for Cooperative Multi-Player Multi-Armed Bandits [PDF]
    William Chang, Mehdi Jafarnia-Jahromi, Rahul Jain
    IEEE Conference on Decision and Control, 2022

Markov Decision Processes

  1. No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions [PDF]
    Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
    Neural Information Processing Systems, 2023

Control Theory

  1. Bode Integral Limitation For Irrational Systems [PDF]
    William Chang, Fariba Ariaei, Edmond Jonckheere
    International Federation of Automatic Control, 2023

Neural Network Theory

  1. Approximation Capabilities of Neural Networks using Morphological Perceptions and Generalizations [PDF]
    William Chang, Hassan Hamad, Keith Chugg
    Asilomar conference on signals, systems, and computers, 2022

Computer Vision

  1. Mixup to the Random Extreme and Its Performances in Robust Image Classification [PDF]
    Jackie Chen, Qianjing Chen, William Chang, Haohan Wang
    Transactions on Machine Learning Research, 2023

Domain Adaptation

  1. Understanding Domain Adaptation in the Lens of Causality[PDF]
    William Chang, Haohan Wang
    Under review at Causal Learning and Reasoning, 2024

Mixing

  1. Mixing on Generalized Associahedra
    William Chang, Colin Defant, Daniel Frishberg
    Under Review at International Symposium on Algorithms and Computation, 2023

Differential Equations

  1. Finite-time singularities in a generalized elastohydrodynamic lubrication equation [PDF]
    William Chang, Hangjie Ji
    Under Review at Applied Mathematics Letters, 2023

Geometry

  1. Compatibility in Ozsvath-Szabo’s bordered HFK via higher representations [PDF]
    William Chang, Andrew Manion
    The Pacific Journal of Mathematics, 2023