AIMS OF THE WORKSHOP

Sparse approximations provide extremely useful tools to solve many signal and image processing problems, from blind source separation to feature extraction and classification, denoising, and detection ...
Yet, they raise numerous challenges and open questions, from data modeling to computational issues.

The purpose of the workshop is to present and discuss novel ideas, works and results, both experimental and theoretical, related to this rapidly evolving area of research.

FOCUS OF THE WORKSHOP

Contributions are expected on the following topics (non-limitative list):

• Sparse coding, vector quantization and dictionary learning
• Sparse approximation algorithms : performance and complexity analysis, new methodologies, ...
• Simultaneous processing of multiple signals/images
• Sparse/structured signal representations, visualization
• Compression and coding
• Feature extraction, classification, detection
• Source separation
• Sparsity measures in approximation theory, information theory and statistics
• Applications to image, audio, video, medical, multimedia and multichannel data processing
• Others

CONTRIBUTIONS

Any communication proposal will mandatorily consist of:

• The paper title;
• The name ot the authors with their complete address (mai and
  email, phone, fax), the name of the principal author being underlined
• The answers to the three questions (with at most 5 lines per question) :
  • statement of the problem
  • originality of the work
  • new results
• A summary of two pages minimum and three pages maximum (single column), including figures.

Final papers format : 4 pages maximum, double column, in PDF, A4, font>= 9pt

The workshop is open in priority to participants who will give a presentation, however participation without a presentation should be possible depending on the number of participants. If you are interested, please contact the organizers in advance to let them know about your intention to participate.

For more informations: spars05@irisa.fr