most citedKernel Alignment Risk Estimator: Risk Prediction from Training Data

23 citations · 40 across the 3 of their papers we have counts for

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stat.ML2021★ 3 cited

Saddle-to-Saddle Dynamics in Deep Linear Networks: Small Initialization Training, Symmetry, and Sparsity

Arthur Jacot, François Ged, Berfin Şimşek +2

The dynamics of Deep Linear Networks (DLNs) is dramatically affected by the variance of the parameters at initialization . For DLNs of width , we show a phase transit…

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…