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Found 2 papers, 1 papers with code
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks
We derive simple closed-form estimates for the test risk and other generalization metrics of kernel ridge regression (KRR).
Neural tangent kernel eigenvalues accurately predict generalization
Finding a quantitative theory of neural network generalization has long been a central goal of deep learning research.
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