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2025 ICML ICML 2025

Position: A Theory of Deep Learning Must Include Compositional Sparsity

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

David A. Danhofer, Davide D’Ascenzo, Rafael Dubach, Tomaso A Poggio

Topics

Artificial Intelligence > Core AI > Interpretability Machine Learning > Optimization & Theory > Learning Theory Deep Learning > Architectures > Neural Networks

Keywords

optimization learnability compositional sparsity constituent functions low-dimensional subset turing-computable functions
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