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Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning
Sharpness-Aware Minimization (SAM) is an optimization method that improves the generalization performance of machine learning models. Despite its effectiveness, it has not been widely adopted in real-world applications due to its high computational cost. Existing approaches reduce this overhead by a
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