Exploring Sharpness-Aware Minimization (SAM): Insights into Label Noise Robustness and Generalization

Recently, there’s been increasing interest in enhancing deep networks’ generalization by regulating loss landscape sharpness. Sharpness Aware Minimization (SAM) has gained popularity for its superior performance on various benchmarks, specifically in managing random label noise, outperforming SGD by significant margins. SAM’s robustness shines particularly in scenarios with label noise, showcasing substantial improvements over existing techniques. […]

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