Neural Collapse with Cross-Entropy Loss

Jianfeng Lu; Stefan Steinerberger

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arXiv · 2012.08465

Neural Collapse with Cross-Entropy Loss

Jianfeng Lu·Stefan Steinerberger

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Abstract

We consider the variational problem of cross-entropy loss with $n$ feature vectors on a unit hypersphere in $\mathbb{R}^d$. We prove that when $d \geq n - 1$, the global minimum is given by the simplex equiangular tight frame, which justifies the neural collapse behavior. We also prove that as $n \rightarrow \infty$ with fixed $d$, the minimizing points will distribute uniformly on the hypersphere and show a connection with the frame potential of Benedetto & Fickus.

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Jianfeng Lu, Stefan Steinerberger. 2020-12-15. Neural Collapse with Cross-Entropy Loss. https://arxiv.org/abs/2012.08465

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