91 citations · 257 across the 9 of their papers we have counts for
4 papers · 1 filter
Learning with convolution and pooling operations in kernel methods
Theodor Misiakiewicz, Song Mei
Recent empirical work has shown that hierarchical convolutional kernels inspired by convolutional neural networks (CNNs) significantly improve the performance of kernel methods in…
Minimum complexity interpolation in random features models
Michael Celentano, Theodor Misiakiewicz, Andrea Montanari
Despite their many appealing properties, kernel methods are heavily affected by the curse of dimensionality. For instance, in the case of inner product kernels in , t…
Learning with invariances in random features and kernel models
Song Mei, Theodor Misiakiewicz, Andrea Montanari
A number of machine learning tasks entail a high degree of invariance: the data distribution does not change if we act on the data with a certain group of transformations. For inst…
Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Consider the classical supervised learning problem: we are given data , , with a response and a covariate…