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cs.LG2024
No More Adam: Learning Rate Scaling at Initialization is All You Need
Minghao Xu, Lichuan Xiang, Xu Cai +1
In this work, we question the necessity of adaptive gradient methods for training deep neural networks. SGD-SaI is a simple yet effective enhancement to stochastic gradient descent…
cs.CV2024
Fast Sampling Through The Reuse Of Attention Maps In Diffusion Models
Rosco Hunter, Łukasz Dudziak, Mohamed S. Abdelfattah +3
Text-to-image diffusion models have demonstrated unprecedented capabilities for flexible and realistic image synthesis. Nevertheless, these models rely on a time-consuming sampling…