4 citations · 5 across the 9 of their papers we have counts for
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cs.LG2025
Taming Latency and Bandwidth: A Theoretical Framework and Adaptive Algorithm for Communication-Constrained Training
Rongwei Lu, Jingyan Jiang, Chunyang Li +2
Regional energy caps limit the growth of any single data center used for large-scale model training. This single-center training paradigm works when model size remains manageable,…
cs.LG2025
-FedHT: Stepsize-Aware Hard-Threshold Gradient Compression in Federated Learning
Rongwei Lu, Yutong Jiang, Jinrui Zhang +4
Gradient compression can effectively alleviate communication bottlenecks in Federated Learning (FL). Contemporary state-of-the-art sparse compressors, such as Top-, exhibit high…
cs.LG2023★ 4 cited
Data-Aware Gradient Compression for FL in Communication-Constrained Mobile Computing
Rongwei Lu, Yutong Jiang, Yinan Mao +4
Federated Learning (FL) in mobile environments faces significant communication bottlenecks. Gradient compression has proven as an effective solution to this issue, offering substan…