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stat.ML2024
Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
Chengshuai Shi, Kun Yang, Jing Yang +1
The in-context learning (ICL) capability of pre-trained models based on the transformer architecture has received growing interest in recent years. While theoretical understanding…
stat.ML2024
Harnessing the Power of Federated Learning in Federated Contextual Bandits
Chengshuai Shi, Ruida Zhou, Kun Yang +1
Federated learning (FL) has demonstrated great potential in revolutionizing distributed machine learning, and tremendous efforts have been made to extend it beyond the original foc…
stat.ML2024
Efficient Prompt Optimization Through the Lens of Best Arm Identification
Chengshuai Shi, Kun Yang, Zihan Chen +3
The remarkable instruction-following capability of large language models (LLMs) has sparked a growing interest in automatically finding good prompts, i.e., prompt optimization. Mos…