2 citations · 5 across the 3 of their papers we have counts for
3 papers
stat.ML2024★ 1 cited
A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator
Theodor Misiakiewicz, Basil Saeed
We consider learning an unknown target function using kernel ridge regression (KRR) given i.i.d. data , , where is a covariate vector and $y_i…
stat.ML2024★ 2 cited
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
Hong Hu, Yue M. Lu, Theodor Misiakiewicz
Recent advances in machine learning have been achieved by using overparametrized models trained until near interpolation of the training data. It was shown, e.g., through the doubl…
stat.ML2023★ 2 cited
Six Lectures on Linearized Neural Networks
Theodor Misiakiewicz, Andrea Montanari
In these six lectures, we examine what can be learnt about the behavior of multi-layer neural networks from the analysis of linear models. We first recall the correspondence betwee…