421 citations · 2.4k across the 51 of their papers we have counts for
7 papers · 1 filter
Multitask diffusion adaptation over asynchronous networks
Roula Nassif, Cédric Richard, André Ferrari +1
The multitask diffusion LMS is an efficient strategy to simultaneously infer, in a collaborative manner, multiple parameter vectors. Existing works on multitask problems assume tha…
A graph Laplacian regularization for hyperspectral data unmixing
Rita Ammanouil, André Ferrari, Cédric Richard
This paper introduces a graph Laplacian regularization in the hyperspectral unmixing formulation. The proposed regularization relies upon the construction of a graph representation…
A stochastic behavior analysis of stochastic restricted-gradient descent algorithm in reproducing kernel Hilbert spaces
Masa-aki Takizawa, Masahiro Yukawa, Cedric Richard
This paper presents a stochastic behavior analysis of a kernel-based stochastic restricted-gradient descent method. The restricted gradient gives a steepest ascent direction within…
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
L. Jacques, C. De Vleeschouwer, Y. Boursier +64
The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between interna…
Diffusion LMS over Multitask Networks
Jie Chen, Cédric Richard, Ali H. Sayed
The diffusion LMS algorithm has been extensively studied in recent years. This efficient strategy allows to address distributed optimization problems over networks in the case wher…
Blind and fully constrained unmixing of hyperspectral images
Rita Ammanouil, André Ferrari, Cédric Richard +1
This paper addresses the problem of blind and fully constrained unmixing of hyperspectral images. Unmixing is performed without the use of any dictionary, and assumes that the numb…