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The Ethereal
Neural collapse with unconstrained features
November 23, 2020 ยท Declared Dead ยท ๐ Sampling Theory, Signal Processing, and Data Analysis
"No code URL or promise found in abstract"
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Authors
Dustin G. Mixon, Hans Parshall, Jianzong Pi
arXiv ID
2011.11619
Category
cs.LG: Machine Learning
Citations
144
Venue
Sampling Theory, Signal Processing, and Data Analysis
Last Checked
4 months ago
Abstract
Neural collapse is an emergent phenomenon in deep learning that was recently discovered by Papyan, Han and Donoho. We propose a simple "unconstrained features model" in which neural collapse also emerges empirically. By studying this model, we provide some explanation for the emergence of neural collapse in terms of the landscape of empirical risk.
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