Recently, flat minima are proven to be effective for improving generalization and sharpness-
aware minimization (SAM) achieves state-of-the-art performance. Yet the current definition of …

Sharpness of minima is a promising quantity that can correlate with generalization in deep
networks and, when optimized during training, can improve generalization. However …

Mamba, a recent selective structured state space model, excels in long sequence modeling,
which is vital in the large model era. Long sequence modeling poses significant challenges …

Abstract Sharpness-Aware Minimization (SAM) has been instrumental in improving deep
neural network training by minimizing both training loss and loss sharpness. Despite the …

Abstract Semi-Supervised Learning (SSL) has been an effective way to leverage abundant
unlabeled data with extremely scarce labeled data. However, most SSL methods are …

Abstract Domain generalization (DG) seeks to learn robust models that generalize well
under unknown distribution shifts. As a critical aspect of DG, optimizer selection has not …

Although deep learning has made great progress in recent years, the exploding economic
and environmental costs of training neural networks are becoming unsustainable. To …