Web: http://arxiv.org/abs/2209.07999

Sept. 19, 2022, 1:14 a.m. | Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik, Deniz Yuret, Alper T. Erdogan

cs.CV updates on arXiv.org arxiv.org

Self-supervised learning allows AI systems to learn effective representations
from large amounts of data using tasks that do not require costly labeling.
Mode collapse, i.e., the model producing identical representations for all
inputs, is a central problem to many self-supervised learning approaches,
making self-supervised tasks, such as matching distorted variants of the
inputs, ineffective. In this article, we argue that a straightforward
application of information maximization among alternative latent
representations of the same input naturally solves the collapse problem and …

arxiv information self-supervised learning supervised learning

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