
Learning with minibatch Wasserstein : asymptotic and gradient properties
Optimal transport distances are powerful tools to compare probability di...
read it

Stable safe screening and structured dictionaries for faster ℓ_1 regularization
In this paper, we propose a way to combine two acceleration techniques f...
read it

Equinormalization of Neural Networks
Modern neural networks are overparametrized. In particular, each rectif...
read it

MULAN: A Blind and OffGrid Method for Multichannel Echo Retrieval
This paper addresses the general problem of blind echo retrieval, i.e., ...
read it

Don't take it lightly: Phasing optical random projections with unknown operators
In this paper we tackle the problem of recovering the phase of complex l...
read it

And the Bit Goes Down: Revisiting the Quantization of Neural Networks
In this paper, we address the problem of reducing the memory footprint o...
read it

Compressive Statistical Learning with Random Feature Moments
We describe a general framework compressive statistical learning for...
read it

SUBIC: A supervised, structured binary code for image search
For largescale visual search, highly compressed yet meaningful represen...
read it

Compressive Kmeans
The LloydMax algorithm is a classical approach to perform Kmeans clust...
read it

Sketching for LargeScale Learning of Mixture Models
Learning parameters from voluminous data can be prohibitive in terms of ...
read it

Compressive Spectral Clustering
Spectral clustering has become a popular technique due to its high perfo...
read it

Random sampling of bandlimited signals on graphs
We study the problem of sampling kbandlimited signals on graphs. We pro...
read it

Approximate search with quantized sparse representations
This paper tackles the task of storing a large collection of vectors, su...
read it

Learning CoSparse Analysis Operators with Separable Structures
In the cosparse analysis model a set of filters is applied to a signal ...
read it

Dynamic Screening: Accelerating FirstOrder Algorithms for the Lasso and GroupLasso
Recent computational strategies based on screening tests have been propo...
read it

Sparse and spurious: dictionary learning with noise and outliers
A popular approach within the signal processing and machine learning com...
read it

On The Sample Complexity of Sparse Dictionary Learning
In the synthesis model signals are represented as a sparse combinations ...
read it

Sample Complexity of Dictionary Learning and other Matrix Factorizations
Many modern tools in machine learning and signal processing, such as spa...
read it

Local stability and robustness of sparse dictionary learning in the presence of noise
A popular approach within the signal processing and machine learning com...
read it

Underdetermined reverberant audio source separation using a fullrank spatial covariance model
This article addresses the modeling of reverberant recording environment...
read it

Learning a Complete Image Indexing Pipeline
To work at scale, a complete image indexing system comprises two compone...
read it

Sketched Clustering via Hybrid Approximate Message Passing
In sketched clustering, the dataset is first sketched down to a vector o...
read it

Instance Optimal Decoding and the Restricted Isometry Property
In this paper, we study the preservation of information in illposed non...
read it

A modeling and algorithmic framework for (non)social (co)sparse audio restoration
We propose a unified modeling and algorithmic framework for audio restor...
read it

On Bayesian Estimation And Proximity Operators
There are two major routes to address the ubiquitous family of inverse p...
read it

Is the 1norm the best convex sparse regularization?
The 1norm is a good convex regularization for the recovery of sparse ve...
read it

Analyzing the Approximation Error of the Fast Graph Fourier Transform
The graph Fourier transform (GFT) is in general dense and requires O(n^2...
read it

Concentration of the Frobenius norms of pseudoinverses
In many applications it is useful to replace the MoorePenrose pseudoinv...
read it

Concentration of the Frobenius norms of generalized matrix inverses
In many applications it is useful to replace the MoorePenrose pseudoinv...
read it

Concentration of the Frobenius norm of generalized matrix inverses
In many applications it is useful to replace the MoorePenrose pseudoinv...
read it

When does OMP achieves support recovery with continuous dictionaries?
This paper presents new theoretical results on sparse recovery guarantee...
read it

When does OMP achieve support recovery with continuous dictionaries?
This paper presents new theoretical results on sparse recovery guarantee...
read it

Approximation spaces of deep neural networks
We study the expressivity of deep neural networks. Measuring a network's...
read it
Rémi Gribonval
is this you? claim profile
Directeur de Recherche / Senior Research Scientist at INRIA, Head of the PANAMA projectteam at IRISA, Blaise Pascal Award of the GAMNISMAI by the French Academy of Sciences, and a starting investigator grant from the European Research Council in 2011, IEEE fellow and a EURASIP Fellow, IEEE SPTM Technical Committee and of the SPARS steering committee.