Understanding MLP-Mixer as a wide and sparse MLP

Tomohiro Hayase; Ryo Karakida

2024 ICML ICML 2024

Understanding MLP-Mixer as a wide and sparse MLP

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

Tomohiro Hayase, Ryo Karakida

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Optimization & Theory > Learning Theory Deep Learning > Architectures > Neural Networks

Keywords

mlp mixer monarch matrice golubeva, neyshabur and gur-ari kronecker-product weights sparseness unstructured sparse-weight mlps

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