2 papers
cs.LG2026
Convergence Bound and Critical Batch Size of Muon Optimizer
Naoki Sato, Hiroki Naganuma, Hideaki Iiduka
Muon, a recently proposed optimizer that leverages the inherent matrix structure of neural network parameters, has demonstrated strong empirical performance, indicating its potenti…
cs.LG2025
Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training
Hiroki Naganuma, Xinzhi Zhang, Man-Chung Yue +4
Following AI scaling trends, frontier models continue to grow in size and continue to be trained on larger datasets. Training these models requires huge investments in exascale com…