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2025 ICML ICML 2025

On the Importance of Embedding Norms in Self-Supervised Learning

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J Bekkers

Topics

Machine Learning > Learning Types > Self-Supervised Learning Machine Learning > Optimization & Theory > Learning Theory Deep Learning > Learning Types > Representation Learning

Keywords

convergence rate cosine similarity embedding norm hyperspheres manipulating norms network confidence
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