SPARS 2017 will be held at Instituto Superior Técnico (IST), the engineering school of the University of Lisbon, on June 5-8, 2017.
All details and updated information at: http://spars2017.lx.it.pt/
The Signal Processing with Adaptive Sparse Structured Representations (SPARS) workshop aims at bringing together people from statistics, engineering, mathematics, and computer science, fostering the exchange and dissemination of new ideas and results, both applied and theoretical, on the general area of sparsity-related techniques and computational methods, for high dimensional data analysis, signal processing, and related applications.
In addition to 8 plenary lectures, the workshop will feature a single track format with approximately 30 standard (20min) talks, and 3 poster/demo sessions.
- Sparse coding and representations, and dictionary learning.
- Sparse and low-rank approximation algorithms.
- Compressive sensing and learning.
- Dimensionality reduction and feature extraction.
- Sparsity measures in approximation theory, information theory, and statistics.
- Low-complexity/low-dimensional regularization.
- Statistical and Bayesian models and algorithms for sparsity.
- Sparse network theory and analysis.
- Sparsity and low-rank regularization.
- Yoram Bresler, Beckman Institute, University of Illinois, USA.
- Volkan Cevher, École polytechnique Fédérale de Lausanne, Switzerland.
- Jalal Fadili, École Nationale Supérieure d'Ingénieurs de Caen, France.
- Anders Hansen, University of Cambridge, UK.
- Gitta Kutyniok, Technische Universität Berlin, Germany.
- Philip Schniter, Ohio State University, USA.
- Eero Simoncelli, Howard Hughes Medical Institute, New York University, USA.
- Rebecca Willett, University of Wisconsin, USA.
- Submission of extended abstracts: December 12, 2016
- Notification of acceptance: March 27, 2017.
- Workshop: June 5-8, 2017.