385 citations · 1.5k across the 64 of their papers we have counts for
6 papers · 1 filter
Astronomical image reconstruction with convolutional neural networks
Rémi Flamary
State of the art methods in astronomical image reconstruction rely on the resolution of a regularized or constrained optimization problem. Solving this problem can be computational…
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…
Wasserstein Discriminant Analysis
Rémi Flamary, Marco Cuturi, Nicolas Courty +1
Wasserstein Discriminant Analysis (WDA) is a new supervised method that can improve classification of high-dimensional data by computing a suitable linear map onto a lower dimensio…
Non-convex regularization in remote sensing
Devis Tuia, Remi Flamary, Michel Barlaud
In this paper, we study the effect of different regularizers and their implications in high dimensional image classification and sparse linear unmixing. Although kernelization or s…
Importance sampling strategy for non-convex randomized block-coordinate descent
Rémi Flamary, Alain Rakotomamonjy, Gilles Gasso
As the number of samples and dimensionality of optimization problems related to statistics an machine learning explode, block coordinate descent algorithms have gained popularity s…
Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
Devis Tuia, Rémi Flamary, Nicolas Courty
In this paper, we tackle the question of discovering an effective set of spatial filters to solve hyperspectral classification problems. Instead of fixing a priori the filters and…