91 citations · 181 across the 6 of their papers we have counts for
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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…
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…
Limitations of Lazy Training of Two-layers Neural Networks
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz +1
We study the supervised learning problem under either of the following two models: (1) Feature vectors are -dimensional Gaussians and responses are $y_i = f_…
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
Song Mei, Theodor Misiakiewicz, Andrea Montanari
We consider learning two layer neural networks using stochastic gradient descent. The mean-field description of this learning dynamics approximates the evolution of the network wei…