activity
20132022
most citedIntegration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing

79 citations · 196 across the 12 of their papers we have counts for

collaborators
Showing 2020 · eess.SPShow all

6 papers · 2 filters

eess.SP2020

Online Graph-Based Change Point Detection in Multiband Image Sequences

Ricardo Augusto Borsoi, Cédric Richard, André Ferrari +2

The automatic detection of changes or anomalies between multispectral and hyperspectral images collected at different time instants is an active and challenging research topic. To…

eess.SP2020

Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion with Inter-Image Variability

Ricardo Augusto Borsoi, Clémence Prévost, Konstantin Usevich +3

Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with st…

eess.SP2020★ 30 cited

Diffusion LMS with Communication Delays: Stability and Performance Analysis

Fei Hua, Roula Nassif, Cédric Richard +2

We study the problem of distributed estimation over adaptive networks where communication delays exist between nodes. In particular, we investigate the diffusion Least-Mean- Square…

eess.SP2020★ 2 cited

Affine Combination of Diffusion Strategies over Networks

Danqi Jin, Jie Chen, Cedric Richard +2

Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a comb…

eess.SP2020

Online change-point detection with kernels

André Ferrari, Cédric Richard, Anthony Bourrier +1

Change-points in time series data are usually defined as the time instants at which changes in their properties occur. Detecting change-points is critical in a number of applicatio…

eess.SP2020

Multitask learning over graphs: An Approach for Distributed, Streaming Machine Learning

Roula Nassif, Stefan Vlaski, Cedric Richard +2

The problem of learning simultaneously several related tasks has received considerable attention in several domains, especially in machine learning with the so-called multitask lea…