arXiv Machine Learning
Jun 9

Convergence Bound and Critical Batch Size of Muon Optimizer

arXiv:2507. 01598v5 Announce Type: replace Abstract: Muon, a recently proposed optimizer that leverages the inherent matrix structure of neural network parameters, has demonstrated strong empirical performance, indicating its potential as a successor to standard optimizers such as AdamW.

By Naoki Sato, Hiroki Naganuma, Hideaki Iiduka