2 papers
cs.LG2024
A Variance Minimization Approach to Temporal-Difference Learning
Xingguo Chen, Yu Gong, Shangdong Yang +1
Fast-converging algorithms are a contemporary requirement in reinforcement learning. In the context of linear function approximation, the magnitude of the smallest eigenvalue of th…
cs.LG2024
MoE-I: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition
Cheng Yang, Yang Sui, Jinqi Xiao +7
The emergence of Mixture of Experts (MoE) LLMs has significantly advanced the development of language models. Compared to traditional LLMs, MoE LLMs outperform traditional LLMs by…