Can We Understand Plasticity Through Neural Collapse?

• URL: http://arxiv.org/abs/2404.02719v1
• Date: Wed, 3 Apr 2024 13:21:58 GMT
• Title: Can We Understand Plasticity Through Neural Collapse?
• Authors: Guglielmo Bonifazi, Iason Chalas, Gian Hess, Jakub Łucki,
• Abstract summary: This paper explores the connection between two recently identified phenomena in deep learning: plasticity loss and neural collapse. We analyze their correlation in different scenarios, revealing a significant association during the initial training phase on the first task. We introduce a regularization approach to mitigate neural collapse, demonstrating its effectiveness in alleviating plasticity loss in this specific setting.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper explores the connection between two recently identified phenomena in deep learning: plasticity loss and neural collapse. We analyze their correlation in different scenarios, revealing a significant association during the initial training phase on the first task. Additionally, we introduce a regularization approach to mitigate neural collapse, demonstrating its effectiveness in alleviating plasticity loss in this specific setting.

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