Learning Towards the Largest Margins. (arXiv:2206.11589v1 [cs.CV])

Web: http://arxiv.org/abs/2206.11589

One of the main challenges for feature representation in deep learning-based
classification is the design of appropriate loss functions that exhibit strong
discriminative power. The classical softmax loss does not explicitly encourage
discriminative learning of features. A popular direction of research is to
incorporate margins in well-established losses in order to enforce extra
intra-class compactness and inter-class separability, which, however, were
developed through heuristic means, as opposed to rigorous mathematical
principles. In this work, we attempt to address this limitation …

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