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cs.LG2026
Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf
Priya Kasimbeg, Ahmed Khaled, Aahlad Chandrabhatta +9
Evaluating deep learning optimizer is challenging because confounding factors such as hyperparameter tuning and optimizer-model co-design often obscure true algorithmic performance…
cs.LG2026
Muon Does Not Converge on Convex Lipschitz Functions
Tetiana Parshakova, Ahmed Khaled, Michael Crawshaw +2
Muon and its variants have shown strong empirical performance in a variety of deep learning tasks. Existing convergence analyses of Muon rely on smoothness assumptions, though argu…