#double-descent News & Analysis

2 articles tagged with #double-descent. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Apr 107/10

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Path Regularization: A Near-Complete and Optimal Nonasymptotic Generalization Theory for Multilayer Neural Networks and Double Descent Phenomenon

Researchers propose a new nonasymptotic generalization theory for multilayer neural networks using path regularization, proving near-minimax optimal error bounds without requiring unbounded loss functions or infinite network dimensions. The theory notably explains the double descent phenomenon and solves an open problem in approximation theory for neural networks.

AINeutralarXiv – CS AI · 15h ago6/10

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Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent

Researchers propose a representation-readout decomposition framework that explains anomalous neural network training phenomena like grokking and double descent by analyzing two competing learning processes: representation learning in encoders and readout calibration in classifiers. The framework provides task-agnostic diagnostics that reveal these phenomena stem from fluctuations in relative learning speeds rather than mysterious delays, challenging existing lazy-to-rich learning theories.