Best Arm Identification in Generalized Linear Bandits via Hybrid Feedback
In Proceedings of the 40th Annual Conference on Neural Information Processing Systems
Ph.D. candidate in Computer Science at City University of Hong Kong
I study learning and decision-making under uncertainty, focusing on bandit learning, feedback design, and adversarial robustness. My interests also include sequential inference and combinatorial optimization. My advisor is Prof. Jinhang Zuo.
Previously, I worked as a research assistant with Prof. Sibo Wang at the Chinese University of Hong Kong from July to October 2024. I received my bachelor’s degree in Computer Science and Technology from the School of the Gifted Young at the University of Science and Technology of China, where I was advised by Prof. Xue Chen and Prof. Jinhang Zuo.
⋆ Equal contribution.
In Proceedings of the 40th Annual Conference on Neural Information Processing Systems
In Proceedings of the 40th Annual Conference on Neural Information Processing Systems
In Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Our paper WEREWOLF: Reputation-Aware Red-Teaming for Self-Organizing LLM Multi-Agent Systems was accepted to Findings of EMNLP 2026.
Our paper One Rounding Fits All: Memory-Efficient Approximation Algorithms for Partition-Constrained Influence Maximization was accepted to KDD 2026.
Reviewer
AISTATS and WWW.
ICLR and NeurIPS.
ICML and NeurIPS.
| Account | Rating | Peak | Solved |
|---|---|---|---|
| Codeforces | 1630 | 1648 | 118 |
| AtCoder | 984 | 1023 | 71 |
| LeetCode | 1920 | 1920 | 116 |
| Luogu | 1216 | 1216 | 82 |
Updated
387 platform solves across 4 accounts
Problems can have multiple topics.
Problems can appear in multiple languages.
Topic coverage: Codeforces and Luogu. Language coverage: Codeforces, AtCoder and LeetCode. Missing data remains visible as Unclassified or Not public.