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cs.LG2026
AMUSE: Anytime Muon with Stable Gradient Evaluation
Jueun Kim, Baekrok Shin, Jihun Yun +3
Modern deep learning commonly relies on AdamW with prescribed learning rate schedules, but recent works challenge both components: Schedule-Free optimization removes explicit sched…
cs.LG2026
Suspicious Alignment of SGD: A Fine-Grained Step Size Condition Analysis
Shenyang Deng, Boyao Liao, Zhuoli Ouyang +3
This paper explores the suspicious alignment phenomenon in stochastic gradient descent (SGD) under ill-conditioned optimization, where the Hessian spectrum splits into dominant and…