48 citations · 175 across the 26 of their papers we have counts for
4 papers · 1 filter
The Gaussian equivalence of generative models for learning with shallow neural networks
Sebastian Goldt, Bruno Loureiro, Galen Reeves +3
Understanding the impact of data structure on the computational tractability of learning is a key challenge for the theory of neural networks. Many theoretical works do not explici…
Information-theoretic limits of a multiview low-rank symmetric spiked matrix model
Jean Barbier, Galen Reeves
We consider a generalization of an important class of high-dimensional inference problems, namely spiked symmetric matrix models, often used as probabilistic models for principal c…
Information-Theoretic Limits for the Matrix Tensor Product
Galen Reeves
This paper studies a high-dimensional inference problem involving the matrix tensor product of random matrices. This problem generalizes a number of contemporary data science probl…
Gaussian Approximation of Quantization Error for Estimation from Compressed Data
Alon Kipnis, Galen Reeves
We consider the distributional connection between the lossy compressed representation of a high-dimensional signal using a random spherical code and the observation of unde…