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2024 ICML ICML 2024

Understanding Unimodal Bias in Multimodal Deep Linear Networks

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

Yedi Zhang, Peter E. Latham, Andrew M Saxe

Topics

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

Keywords

unimodal bia dataset statistics fusion depth generalization deficit multimodal deep linear networks overparametrized regime
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