We have a new preprint on Compressive K-Means.
Read it on https://hal.inria.fr/hal-01386077
Download the code at http://sketchml.gforge.inria.fr/
Details and appliication here
Congratulations to Antoine Deleforge (new PANAMA team member), Florence Forbes (MISTIS team) and Radu Horaud (PERCEPTION team) who received the 2016 Hojjat Adeli Award for Outstanding Contributions in Neural Systems for their paper:
The Award for Outstanding Contributions in Neural Systems established by World Scientific Publishing Co. in 2010, is awarded annually to the most innovative paper published in the previous volume/year of the International Journal of Neural Systems.
For more information concerning this paper please visit the page of the PERCEPTION team on Acoustic Space Learning on Binaural Manifolds (article download, Matlab code, datasets, etc.)
Details and application here
FaµST (pronounce FAUST) yields computationnaly efficient approximations to large dense matrices that can speed up iterative solvers for large-scale linear inverse problems.
See details on the methodology behind FaµST and some other applications, in our paper Le Magoarou L. and Gribonval R., “Flexible multi-layer sparse approximations of matrices and applications”, Journal of Selected Topics in Signal Processing, 2016.
Download the code at http://faust.gforge.inria.fr/ and … stay tuned for the upcoming C++ FaµST library.
The French-speaking journal “Traitement du Signal” publishes this trimester a special issue on the theme of Multimodality and New Interactions in Music Signal Processing (“Traitement Des Signaux Musicaux Multimodalité Et Nouvelles Interactions”), coordinated by Nancy BERTIN, Frédéric BIMBOT, Jules ESPIAU DE LAMAËSTRE and Anaïk OLIVERO, members or former members of PANAMA team.
All articles published in this issue include a one-page abstract in English.
The PANAMA team @ Inria, Rennes, France is seeking highly qualified post-doctoral candidates to contribute to the development of a general theoretic and algorithmic framework for compressive statistical learning, by leveraging concepts from compressive sensing and graph signal processing.
Candidates should hold a Ph.D. in applied mathematics, statistics, theoretical computer science, or mathematical signal processing.
Details and application form here.
Multi-channel BSS Locate is a Matlab toolbox to estimate direction of arrival (expressed both in azimuth and elevation) of multiple sources in a multi-channel audio signal recorded by an array of microphones. This toolbox implements the previous 8 angular spectrum methods available in BSS Locate toolbox.
Online version (no Matlab required):