SPARS 2015

Signal Processing with Adaptive Sparse Structured Representations

July 6-9, 2015, Cambridge, UK.

This website is still provisional and some pages contain missing or to-be-announced (TBA) details of the workshop.

Welcome to the SPARS 2015 website!

Please join us for SPARS 2015 in beautiful and exciting Cambridge, UK.

The Signal Processing with Adaptive Sparse Structured Representations SPARS workshop seeks novel ideas and results, both experimental and theoretical, for adaptive sparse representations, sampling and computational methods for high-dimensional data that feature structured combinatorial and geometric foundations.

SPARS 2015 will take place at Robinson College, Cambridge, from July 6th to July 9th, 2015 and we welcome you!

Important Dates

  • Submission of Paper Abstracts: January 13, 2015
  • Notification of Acceptance of Papers: April 22, 2015
  • Workshop Dates: July 6th to July 9th, 2015

Topics of interest:

  • Sparse coding and representations, vector quantization, and dictionary learning.
  • Sparse and low-rank approximation algorithms: performance and complexity analysis, new methodologies.
  • Compressive sensing and learning: new theory and methods.
  • Dimensionality reduction, feature extraction, classification, detection, and source separation.
  • Sparsity measures in approximation theory, information theory and statistics.
  • Regularization theory with low-complexity / low-dimensional structures.
  • Statistical models and algorithms for sparsity, including Bayesian, likelihood-based, entropy and variational Bayes.
  • Sparse network theory and analysis, including dynamic (time-varying) networks and large networks.
  • Applications of sparsity and low-rank ideas to areas such as 'recovery without phase' and inverse covariance estimation.
  • Big data applications, including but not limited to geophysics, neuroscience, biomedical imaging, array processing, genetics, optics and radar, and feedback control.

Plenary Speakers

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Special Lecture on ... :

Previous SPARS events

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