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stat.ML2020★ 23 cited
Kernel Alignment Risk Estimator: Risk Prediction from Training Data
Arthur Jacot, Berfin Şimşek, Francesco Spadaro +2
We study the risk (i.e. generalization error) of Kernel Ridge Regression (KRR) for a kernel with ridge and i.i.d. observations. For this, we introduce two objects: the Si…
stat.ML2020★ 8 cited
Implicit Regularization of Random Feature Models
Arthur Jacot, Berfin Şimşek, Francesco Spadaro +2
Random Feature (RF) models are used as efficient parametric approximations of kernel methods. We investigate, by means of random matrix theory, the connection between Gaussian RF m…