arxiv
PublishedJune 2, 2026 at 4:00 AM
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Towards Simple and Provable Parameter-Free Adaptive Gradient Methods
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arXiv:2412.19444v2 Announce Type: replace Abstract: Optimization algorithms such as AdaGrad and Adam have significantly advanced the training of deep models by dynamically adjusting the learning rate during the optimization process. However, ad-hoc tuning of learning rates poses a challenge and lead
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Originally published on arxiv ↗