news | Kun Yang

Sep 25, 2024	I’m thrilled to share that two of our papers have been accepted to NeurIPS 2024, with online version and videos coming soon. Looking forward to see you in Vancouver! Efficient Prompt Optimization Through the Lens of Best Arm Identification! (Co-first author): This is a work together with Dr. Chengshuai Shi (Bloomberg, UVA), Zihan Chen (UVA), Prof. Jundong Li (UVA), Prof. Cong Shen (UVA) and Prof. Jing Yang (PSU). Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models: This is a work together with Dr. Chengshuai Shi (Bloomberg, UVA), Prof. Cong Shen (UVA) and Prof. Jing Yang (PSU).
Sep 18, 2024	My accepted paper Average Reward Reinforcement Learning for Wireless Radio Resource Management to IEEE Asilomar 2024, together with Prof. Cong Shen (UVA) and Prof. Jing Yang (PSU), have joined the finalist of the Best student paper award.
Jun 15, 2024	Our paper, Harnessing the Power of Federated Learning in Federated Contextual Bandits!, co-authored with Chengshuai Shi (UVA), Ruida Zhou (UCLA), and Cong Shen (UVA), has been accepted by Transactions on Machine Learning Research (TMLR).
May 17, 2024	Our work on utilizing offline RL for wireless communication has been accepted for publication in IEEE. Transaction on Wireless Communication. Check the manuscipt here!
Feb 15, 2024	Suffering with the budget constraint while selecting the best prompt for your LLM? Check out recent work: Best Arm Identification for Prompt Learning under a Limited Budget!
Feb 4, 2024	Our work Advancing RAN Slicing with Offline Reinforcement Learning has been accepted by Dyspan 2024, see you in D.C.!
Dec 12, 2023	We will present our resent work Harnessing the Power of Federated Learning in Federated Contextual Bandits at MASEC@NeurIPS’23, please come and take a look here.