10 citations · 19 across the 2 of their papers we have counts for
15 papers
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, Florent Krzakala +1
A recent series of theoretical works showed that the dynamics of neural networks with a certain initialisation are well-captured by kernel methods. Concurrent empirical work demons…
The planted -factor problem
Gabriele Sicuro, Lenka Zdeborová
We consider the problem of recovering an unknown -factor, hidden in a weighted random graph. For this is the planted matching problem, while the case is closely rela…
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota +3
Despite the widespread use of gradient-based algorithms for optimizing high-dimensional non-convex functions, understanding their ability of finding good minima instead of being tr…
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová
We study the dynamics of optimization and the generalization properties of one-hidden layer neural networks with quadratic activation function in the over-parametrized regime where…
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Benjamin Aubin, Florent Krzakala, Yue M. Lu +1
We consider a commonly studied supervised classification of a synthetic dataset whose labels are generated by feeding a one-layer neural network with random iid inputs. We study th…
Phase retrieval in high dimensions: Statistical and computational phase transitions
Antoine Maillard, Bruno Loureiro, Florent Krzakala +1
We consider the phase retrieval problem of reconstructing a -dimensional real or complex signal from (possibly noisy) observations $Y_μ= | \sum_{i=1}^n…