24 citations · 52 across the 16 of their papers we have counts for
5 papers · 1 filter
A Gentle Introduction to Gradient-Based Optimization and Variational Inequalities for Machine Learning
Neha S. Wadia, Yatin Dandi, Michael I. Jordan
The rapid progress in machine learning in recent years has been based on a highly productive connection to gradient-based optimization. Further progress hinges in part on a shift i…
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective
Davide Ghio, Yatin Dandi, Florent Krzakala +1
Recent years witnessed the development of powerful generative models based on flows, diffusion or autoregressive neural networks, achieving remarkable success in generating data fr…
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Yatin Dandi, Florent Krzakala, Bruno Loureiro +2
For high-dimensional Gaussian data, we investigate theoretically how the features of a two-layer neural network adapt to the structure of the target function through a few large ba…
Maximally-stable Local Optima in Random Graphs and Spin Glasses: Phase Transitions and Universality
Yatin Dandi, David Gamarnik, Lenka Zdeborová
We consider -stable local optima of Ising spin glass models, defined as spin configurations such that for nearly all of the spins, flipping their values results in increasing en…
Universality laws for Gaussian mixtures in generalized linear models
Yatin Dandi, Ludovic Stephan, Florent Krzakala +2
Let denote independent samples from a general mixture distribution , and consider the hypothesis class of gener…