3 citations · 7 across the 21 of their papers we have counts for
5 papers · 1 filter
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti +1
This work introduces the first toolkit around path-norms that fully encompasses general DAG ReLU networks with biases, skip connections and any operation based on the extraction of…
Butterfly factorization by algorithmic identification of rank-one blocks
Léon Zheng, Gilles Puy, Elisa Riccietti +2
Many matrices associated with fast transforms posess a certain low-rank property characterized by the existence of several block partitionings of the matrix, where each block is of…
Does a sparse ReLU network training problem always admit an optimum?
Quoc-Tung Le, Elisa Riccietti, Rémi Gribonval
Given a training set, a loss function, and a neural network architecture, it is often taken for granted that optimal network parameters exist, and a common practice is to apply ava…
A Block-Coordinate Approach of Multi-level Optimization with an Application to Physics-Informed Neural Networks
Serge Gratton, Valentin Mercier, Elisa Riccietti +1
Multi-level methods are widely used for the solution of large-scale problems, because of their computational advantages and exploitation of the complementarity between the involved…
IML FISTA: A Multilevel Framework for Inexact and Inertial Forward-Backward. Application to Image Restoration
Guillaume Lauga, Elisa Riccietti, Nelly Pustelnik +1
This paper presents a multilevel framework for inertial and inexact proximal algorithms, that encompasses multilevel versions of classical algorithms such as forward-backward and F…