Feature learning in deep classifiers through Intermediate Neural Collapse
In this paper, we conduct an empirical study of the feature learning process in deep classifiers. Recent research has identified a training phenomenon called Neural Collapse (NC), in which the top-layer feature embeddings of samples from the same class tend to concentrate around their means, and the...
| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Center for Brains, Minds and Machines (CBMM)
2023
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| Online Access: | https://hdl.handle.net/1721.1/148239 |