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cs.LG2025
Transformers Meet In-Context Learning: A Universal Approximation Theory
Gen Li, Yuchen Jiao, Yu Huang +2
Large language models are capable of in-context learning, the ability to perform new tasks at test time using a handful of input-output examples, without parameter updates. We deve…
cs.LG2024
Minimax-Optimal Multi-Agent Robust Reinforcement Learning
Yuchen Jiao, Gen Li
Multi-agent robust reinforcement learning, also known as multi-player robust Markov games (RMGs), is a crucial framework for modeling competitive interactions under environmental u…
cs.LG2019★ 3 cited
Compressed Subspace Learning Based on Canonical Angle Preserving Property
Yuchen Jiao, Gen Li, Yuantao Gu
Union of Subspaces (UoS) is a popular model to describe the underlying low-dimensional structure of data. The fine details of UoS structure can be described in terms of canonical a…