3 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- École Normale Supérieure de LyonFR6 papers
- Unité de Mathématiques Pures et AppliquéesFR3 papers
- Valeo (France)FR3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Hôpital Aristide Le DantecSN2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Laboratoire de l'Informatique du ParallélismeFR2 papers
- Laboratoire de Physique de l'ENS de LyonFR2 papers
- Lyon 1 UniversitéFR2 papers
- Agruicultural Research InstituteCY1 paper
- Federico Santa María Technical UniversityCL1 paper
- i2CATES1 paper
15 papers
A flexible block-coordinate forward-backward algorithm for non-smooth and non-convex optimization
Luis Briceño-Arias, Paulo Gonçalves, Guillaume Lauga +2
Block coordinate descent (BCD) methods are prevalent in large scale optimization problems due to the low memory and computational costs per iteration, the predisposition to paralle…
Can sparsity improve the privacy of neural networks?
Antoine Gonon, Léon Zheng, Clément Lalanne +3
Sparse neural networks are mainly motivated by ressource efficiency since they use fewer parameters than their dense counterparts but still reach comparable accuracies. This articl…
Private Statistical Estimation of Many Quantiles
Clément Lalanne, Aurélien Garivier, Rémi Gribonval
This work studies the estimation of many statistical quantiles under differential privacy. More precisely, given a distribution and access to i.i.d. samples from it, we study the e…
Multilevel fista for image restoration
Guillaume Lauga, Elisa Riccietti, Nelly Pustelnik +1
This paper presents a multilevel FISTA algorithm, based on the use of the Moreau envelope to build the correction brought by the coarse models, which is easy to compute when the ex…
On the Statistical Complexity of Estimation and Testing under Privacy Constraints
Clément Lalanne, Aurélien Garivier, Rémi Gribonval
The challenge of producing accurate statistics while respecting the privacy of the individuals in a sample is an important area of research. We study minimax lower bounds for class…
Self-supervised learning with rotation-invariant kernels
Léon Zheng, Gilles Puy, Elisa Riccietti +2
We introduce a regularization loss based on kernel mean embeddings with rotation-invariant kernels on the hypersphere (also known as dot-product kernels) for self-supervised learni…
Compressive Clustering with an Optical Processing Unit
Luc Giffon, Rémi Gribonval
We explore the use of Optical Processing Units (OPU) to compute random Fourier features for sketching, and adapt the overall compressive clustering pipeline to this setting. We als…
Approximation speed of quantized vs. unquantized ReLU neural networks and beyond
Antoine Gonon, Nicolas Brisebarre, Rémi Gribonval +1
We deal with two complementary questions about approximation properties of ReLU networks. First, we study how the uniform quantization of ReLU networks with real-valued weights imp…
Private Quantiles Estimation in the Presence of Atoms
Clément Sébastien Lalanne, Clément Gastaud, Nicolas Grislain +2
We consider the differentially private estimation of multiple quantiles (MQ) of a distribution from a dataset, a key building block in modern data analysis. We apply the recent non…
A theory of optimal convex regularization for low-dimensional recovery
Yann Traonmilin, Rémi Gribonval, Samuel Vaiter
We consider the problem of recovering elements of a low-dimensional model from under-determined linear measurements. To perform recovery, we consider the minimization of a convex r…
Spurious Valleys, NP-hardness, and Tractability of Sparse Matrix Factorization With Fixed Support
Quoc-Tung Le, Elisa Riccietti, Rémi Gribonval
The problem of approximating a dense matrix by a product of sparse factors is a fundamental problem for many signal processing and machine learning tasks. It can be decomposed into…
Identifiability in Two-Layer Sparse Matrix Factorization
Léon Zheng, Elisa Riccietti, Rémi Gribonval
Sparse matrix factorization is the problem of approximating a matrix by a product of sparse factors .…
Efficient Identification of Butterfly Sparse Matrix Factorizations
Léon Zheng, Elisa Riccietti, Rémi Gribonval
Fast transforms correspond to factorizations of the form , where each factor is sparse and possibly st…
Revisiting Open eXchange Points with Software Defined Networking
Pier Luigi Ventre, Bojan Jakovljevic, David Schmitz +6
The introduction of SDN in Service Providers' networks like GEANT is a challenging task. Prototypes of new generation services have to exhibit "carrier grade" characteristics, meet…
Physics-Based Swarm Intelligence for Disaster Relief Communications
Laurent Reynaud, Isabelle Guerin-Lassous
This study explores how a swarm of aerial mobile vehicles can provide network connectivity and meet the stringent requirements of public protection and disaster relief operations.…