125 citations · 443 across the 8 of their papers we have counts for
8 papers
Optimization of the dynamic transition in the continuous coloring problem
Angelo Giorgio Cavaliere, Thibault Lesieur, Federico Ricci-Tersenghi
Random constraint satisfaction problems can exhibit a phase where the number of constraints per variable makes the system solvable in theory on the one hand, but also makes the…
Adversarial training for predictive tasks: theoretical analysis and limitations in the deterministic case
Thibault Lesieur, Jérémie Messud, Issa Hammoud +3
To train a deep neural network to mimic the outcomes of processing sequences, a version of Conditional Generalized Adversarial Network (CGAN) can be used. It has been observed by o…
Statistical and computational phase transitions in spiked tensor estimation
Thibault Lesieur, Léo Miolane, Marc Lelarge +2
We consider tensor factorizations using a generative model and a Bayesian approach. We compute rigorously the mutual information, the Minimal Mean Squared Error (MMSE), and unveil…
Constrained Low-rank Matrix Estimation: Phase Transitions, Approximate Message Passing and Applications
Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
This article is an extended version of previous work of the authors [40, 41] on low-rank matrix estimation in the presence of constraints on the factors into which the matrix is fa…
Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering
Thibault Lesieur, Caterina De Bacco, Jess Banks +3
We consider the problem of Gaussian mixture clustering in the high-dimensional limit where the data consists of points in dimensions, and …
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula
Jean Barbier, Mohamad Dia, Nicolas Macris +3
Factorizing low-rank matrices has many applications in machine learning and statistics. For probabilistic models in the Bayes optimal setting, a general expression for the mutual i…
MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel
Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
This paper considers probabilistic estimation of a low-rank matrix from non-linear element-wise measurements of its elements. We derive the corresponding approximate message passin…
Phase Transitions in Sparse PCA
Thibault Lesieur, Florent Krzakala, Lenka Zdeborova
We study optimal estimation for sparse principal component analysis when the number of non-zero elements is small but on the same order as the dimension of the data. We employ appr…