Muon emerges as strong optimizer for deep learning, outperforming Adam and AdamW; theoretical work interprets it as steepest descent under spectral norm.
Read the original at arxiv.org→arXiv:2607.13246v1 Announce Type: new Abstract: Muon has recently emerged as a strong optimizer for large-scale deep learning, where it reshapes gradient updates through approximate orthogonalization and has been...
Original headline: "Reassessing Muon for Matrix Factorization"