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cs.LG2025
Cautious Weight Decay
Lizhang Chen, Jonathan Li, Kaizhao Liang +6
We introduce Cautious Weight Decay (CWD), a one-line, optimizer-agnostic modification that applies weight decay only to parameter coordinates whose signs align with the optimizer u…
cs.LG2024
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training
Jinda Jia, Cong Xie, Hanlin Lu +8
Recent years have witnessed a clear trend towards language models with an ever-increasing number of parameters, as well as the growing training overhead and memory usage. Distribut…
cs.LG2024
Distributed Sign Momentum with Local Steps for Training Transformers
Shuhua Yu, Ding Zhou, Cong Xie +4
Pre-training Transformer models is resource-intensive, and recent studies have shown that sign momentum is an efficient technique for training large-scale deep learning models, par…