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.
SPARS 2017 will be held
at Instituto Superior Técnico
(IST), the engineering school of the
University of Lisbon, on June 5-8, 2017.
In addition to 8 plenary lectures, the
workshop will feature a single track
format with approximately 30 standard
(20min) talks, and 3 poster/demo
is now closed.
Sparse coding and
representations, and dictionary learning.
low-rank approximation algorithms.
sensing and learning.
reduction and feature extraction.
approximation theory, information theory, and
Bayesian models and algorithms for sparsity.
theory and analysis.
Beckman Institute, University of Illinois, USA.
École Polytechnique Fédérale de Lausanne,
École Nationale Supérieure d'Ingénieurs de Caen,
University of Cambridge, UK.
Universität Berlin, Germany.
Ohio State University, USA.
Howard Hughes Medical Institute, New York
University of Wisconsin, USA.
deadline: December 12, 2016 January 3, 2017
acceptance: March 27, 2017
May 31 - June 2, 2017
June 5-8, 2017
Técnico, University of Lisbon, Portugal
University of Surrey, UK
University of Surrey, UK.
A SpaRTan/MacSeNet Summer
School on Sparse Representations will be
organized during the week before SPARS 2017.
More information will follow shortly.