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cs.LG2025
An All-Reduce Compatible Top-K Compressor for Communication-Efficient Distributed Learning
Chuyan Chen, Chenyang Ma, Zhangxin Li +3
Communication remains a central bottleneck in large-scale distributed machine learning, and gradient sparsification has emerged as a promising strategy to alleviate this challenge.…
cs.LG2025
Greedy Low-Rank Gradient Compression for Distributed Learning with Convergence Guarantees
Chuyan Chen, Yutong He, Pengrui Li +2
Distributed optimization is pivotal for large-scale signal processing and machine learning, yet communication overhead remains a major bottleneck. Low-rank gradient compression, in…