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cs.LG2025
Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
Bing Liu, Boao Kong, Limin Lu +2
Decentralized learning often involves a weighted global loss with heterogeneous node weights . We revisit two natural strategies for incorporating these weights: (i) embedding t…
math.OC2025
Clapping: Removing Per-sample Storage for Pipeline Parallel Distributed Optimization with Communication Compression
Boao Kong, Xu Huang, Yuqi Xu +3
Pipeline-parallel distributed optimization is essential for large-scale machine learning but is challenged by significant communication overhead from transmitting high-dimensional…
cs.LG2025
CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure
Boao Kong, Junzhu Liang, Yuxi Liu +2
Low-rank architectures have become increasingly important for efficient large language model (LLM) pre-training, providing substantial reductions in both parameter complexity and m…