217 citations · 1.4k across the 33 of their papers we have counts for
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cs.LG2021★ 4 cited
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks
James B. Simon, Madeline Dickens, Dhruva Karkada +1
We derive simple closed-form estimates for the test risk and other generalization metrics of kernel ridge regression (KRR). Relative to prior work, our derivations are greatly simp…
cs.LG2021★ 1 cited
Reverse Engineering the Neural Tangent Kernel
James B. Simon, Sajant Anand, Michael R. DeWeese
The development of methods to guide the design of neural networks is an important open challenge for deep learning theory. As a paradigm for principled neural architecture design,…