35 citations · 81 across the 22 of their papers we have counts for
3 papers · 1 filter
On Learning Gaussian Multi-index Models with Gradient Flow
Alberto Bietti, Joan Bruna, Loucas Pillaud-Vivien
We study gradient flow on the multi-index regression problem for high-dimensional Gaussian data. Multi-index functions consist of a composition of an unknown low-rank linear projec…
On Single Index Models beyond Gaussian Data
Joan Bruna, Loucas Pillaud-Vivien, Aaron Zweig
Sparse high-dimensional functions have arisen as a rich framework to study the behavior of gradient-descent methods using shallow neural networks, showcasing their ability to perfo…
Kernelized Diffusion maps
Loucas Pillaud-Vivien, Francis Bach
Spectral clustering and diffusion maps are celebrated dimensionality reduction algorithms built on eigen-elements related to the diffusive structure of the data. The core of these…