Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations
Existing research often posits spurious features as easier to learn than core features in neural network optimization, but the impact of their relative simplicity remains under-explored. Moreover, studies mainly focus on end performance rather than the learning dynamics of feature learning. In this...
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Veröffentlicht in: | arXiv.org 2024-08 |
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Sprache: | eng |
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