Kun Wang
Ph.D. Student
Department of Computer Science
Purdue University
About me
Welcome to my homepage! I am a Ph.D. Student in the Department of Computer Science of Purdue University. I am fortunately advised by Prof. Paul Valiant and Prof. Steve Hanneke. I am interested in theoretical computer science. Previously, I also have some experience on multi-armed bandit, differential privacy, information and coding theory, optimization theory, reinforcement learning theory, game theory and cryptography.
Education
- Ph.D. in Computer Science, Purdue University, 2022 - present
- M.Sc. in Computer Science, Shanghai Jiao Tong University, 2019 - 2022
- B.Eng. in Information Security, Xidian University, 2015 - 2019
Publications
- (α-β)Steve Hanneke, Kun Wang
A Complete Characterization of Learnability for Stochastic Noisy Bandits.(Arxiv)
- (α-β)Simina Brânzei, MohammadTaghi Hajiaghayi, Reed Phillips, Suho Shin, Kun Wang
Dueling over Dessert, Mastering the Art of Repeated Cake Cutting (NeurIPS 2024).
- Kun Wang, Jing Dong, Baoxiang Wang, Shuai Li
Cascading Bandit under Differential Privacy (ICASSP 2022).
- Kun Wang
Conservative Contextual Combinatorial Cascading Bandit (IEEE Access Volume 9, 2021).