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Generalized Cauchy-Schwarz Divergence and Its Deep Learning Applications
May 8, 2024, 4:42 a.m. | Mingfei Lu, Shujian Yu, Robert Jenssen, Badong Chen
cs.LG updates on arXiv.org arxiv.org
Abstract: Divergence measures play a central role in machine learning and become increasingly essential in deep learning. However, valid and computationally efficient divergence measures for multiple (more than two) distributions are scarcely investigated. This becomes particularly crucial in areas where the simultaneous management of multiple distributions is both unavoidable and essential. Examples include clustering, multi-source domain adaptation or generalization, and multi-view learning, among others. Although calculating the mean of pairwise distances between any two distributions serves …
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