26 citations · 94 across the 8 of their papers we have counts for
9 papers
(Dis)assortative Partitions on Random Regular Graphs
Freya Behrens, Gabriel Arpino, Yaroslav Kivva +1
We study the problem of assortative and disassortative partitions on random -regular graphs. Nodes in the graph are partitioned into two non-empty groups. In the assortative par…
Theoretical characterization of uncertainty in high-dimensional linear classification
Lucas Clarté, Bruno Loureiro, Florent Krzakala +1
Being able to reliably assess not only the \emph{accuracy} but also the \emph{uncertainty} of models' predictions is an important endeavour in modern machine learning. Even if the…
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro +2
Despite the non-convex optimization landscape, over-parametrized shallow networks are able to achieve global convergence under gradient descent. The picture can be radically differ…
Error Scaling Laws for Kernel Classification under Source and Capacity Conditions
Hugo Cui, Bruno Loureiro, Florent Krzakala +1
We consider the problem of kernel classification. While worst-case bounds on the decay rate of the prediction error with the number of samples are known for some classifiers, they…
Aligning random graphs with a sub-tree similarity message-passing algorithm
Giovanni Piccioli, Guilhem Semerjian, Gabriele Sicuro +1
The problem of aligning Erdös-Rényi random graphs is a noisy, average-case version of the graph isomorphism problem, in which a pair of correlated random graphs is observed through…
Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising
Antoine Maillard, Florent Krzakala, Marc Mézard +1
Factorization of matrices where the rank of the two factors diverges linearly with their sizes has many applications in diverse areas such as unsupervised representation learning,…