Sparse and Low Rank Approximation (11w5036)


Gitta Kutyniok (LMU Munich)

(RWTH Aachen University)

Joel Tropp (California Institute of Technology)

Ozgur Yilmaz (University of British Columbia)


The Banff International Research Station will host the "Sparse and Low Rank Approximation" workshop from March 6 to 11, 2011.

Digital computers and their efficiency at processing data play a central role in our modern technology. Today, we use digital hardware in every aspect of our daily lives. Cell phones, digital cameras, MP3 players and DVD players are only a few examples where signals of interest, which are inherently analog,are acquired, converted to digital bit-streams, stored in compressed form, and transmitted over noisy channels. In all these applications, the current demand is towards "higher-resolution" and "faster". In turn, the amounts of data we need to deal with is getting exceedingly large.

Recently, a new signal processing paradigm based on "sparsity" has emerged. This new paradigm exploits an empirical observation: many types of signals, e.g., audio, natural images, and video, can be well represented by "very few" elements of a suitable representation system. This fact has revolutionized
data processing, and led to a rethinking about how to acquire various types of signals using a very limited amount of linear measurements. Consequently, this new paradigm has the potential to change the way we collect information about many types of signals. One exciting development is the introduction of the method of Compressed Sensing which, for instance, led to the design of a single-pixel digital camera built at the Rice University, see This research area is very new and hence various key research questions are still under investigation, and also the application
of these techniques to, for instance, astronomical image and signal processing, radar imaging, wireless communication, and seismology is just in its beginning stage. Advancing research on these questions as well as studying the potential for diverse applications is a primary motivation for this workshop.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).