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What is Mechanism of Feature Learning in Neural Networks about?

This paper aims to characterize the mechanism through which deep neural networks learn features from data. The paper proposes that neural feature learning occurs through progressively upweighting features based on their influence on predictions, which can be captured by the average gradient outer product. The paper demonstrates this mechanism leads neural networks to learn meaningful features and can enable feature learning in other machine learning models.

Author

Roshan Raju

Language

EN