70 citations · 89 across the 7 of their papers we have counts for
7 papers
Straight-Through meets Sparse Recovery: the Support Exploration Algorithm
Mimoun Mohamed, François Malgouyres, Valentin Emiya +1
The {\it straight-through estimator} (STE) is commonly used to optimize quantized neural networks, yet its contexts of effective performance are still unclear despite empirical suc…
QuicK-means: Acceleration of K-means by learning a fast transform
Luc Giffon, Valentin Emiya, Liva Ralaivola +1
K-means -- and the celebrated Lloyd algorithm -- is more than the clustering method it was originally designed to be. It has indeed proven pivotal to help increase the speed of man…
Recovery and convergence rate of the Frank-Wolfe Algorithm for the m-EXACT-SPARSE Problem
Farah Cherfaoui, Valentin Emiya, Liva Ralaivola +1
We study the properties of the Frank-Wolfe algorithm to solve the m-EXACT-SPARSE reconstruction problem, where a signal y must be expressed as a sparse linear combination of a pred…
Frank-Wolfe Algorithm for the Exact Sparse Problem
Farah Cherfaoui, Valentin Emiya, Liva Ralaivola +1
In this paper, we study the properties of the Frank-Wolfe algorithm to solve the \ExactSparse reconstruction problem. We prove that when the dictionary is quasi-incoherent, at each…
Phase inpainting in time-frequency plane
A. ~Marina Krémé, Valentin Emiya, Caroline Chaux
We propose a new problem of missing data reconstruction in the time-frequency plane. This problem called phase inpainting, consists in reconstructing a signal from time-frequency o…
Optimal spectral transportation with application to music transcription
Rémi Flamary, Cédric Févotte, Nicolas Courty +1
Many spectral unmixing methods rely on the non-negative decomposition of spectral data onto a dictionary of spectral templates. In particular, state-of-the-art music transcription…
Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso
Antoine Bonnefoy, Valentin Emiya, Liva Ralaivola +1
Recent computational strategies based on screening tests have been proposed to accelerate algorithms addressing penalized sparse regression problems such as the Lasso. Such approac…