Gérard Favier (team SIS, I3S) co-organizes with A. de Almeida (UFC, Brazil) and R. Boyer (L2S, France) a special session for EUSIPCO 2017 : "Advanced Tensor Methods for Big Data Processing"

Date: from 2017-08-28 to 2017-09-02 
http://www.eusipco2017.org/special-sessions/

From Internet to large research infrastructures, the volume of data generated by our societies is continuously increasing. A deluge faced by the producers of these data as well as their users. The big data issue is a significant scientific challenge that requires deep investigations in
both engineering and fundamental science. Everyone is concerned and it is urgent to get answers to questions such as how to store these huge amounts of data? How to process and analyze them? Recently, low-rank tensor methods, including low-rank tensor recovery and completion, new
decompositions, and distributed/online adaptation algorithms have received a particular attention, as solutions to a variety of mining tasks that are increasingly being applied to massive datasets. 

This session proposal aims at gathering recent advances on tensor-based methods that deal with large-scale problems. The invited contributions deal with a variety of problems, such as low-rank decomposition of incomplete tensors, updating algorithms for big data tensors, large tensor spectral theory and performance limits or coupled tensor factorizations for fusion of data models. This session offers a good balance between theoretical findings and applications. Moreover, its structure targets not only the researchers that work in the field but may attract interest from the general audience of EUSIPCO that is aware of the relevance of big data signal processing.