Tutorial video by
Jin Tan and
Yanting Ma
about our research on compressive imaging and approximate
message passing. The video surveys two algorithmic works.
The first reconstructs a message measured noisily with linear
measurements; applications include medical imaging and radio astronomy.
The second reconstructs a hyper spectral cube acquired noisily
by a compressive hyper spectral system, for example the well-known CASSI system
(July 2015).

Tutorial video by
Yanting Ma and
Junan Zhu
about our research on universal denoising and approximate
message passing. This algorithm solves linear inverse problems
in a universal way without knowing the input statistics. (July 2015).

Tutorial video by
Junan Zhu
about our research on size- and level- adaptive
Markov chain Monte Carlo, which is an algorithm
that solves linear inverse problems in a universal
way without knowing the input statistics. (July 2015).

Tutorial video by
Nikhil Krishnan
about our research on parallel algorithms for universal compression
(July 2015).

Tutorial video
by Jin Tan
about our work on signal reconstruction with additive
error metrics (December 2013).

Video advertising a conference presentation at the ITA Workshop;
February
2013.

An MCMC Approach to Lossy Compression of Analog Sources (seminar
talk):
North Carolina State University, September 2010.

Compressed Sensing meets Information Theory
(seminar talk):
Google Research,
Mountain View, CA, October 2009
(Slides).

Compressed Sensing (seminar talk):
Computer Systems Colloquium,
Stanford University, Stanford, CA,
October 18, 2006
(Slides).

Recent Results in Non-Asymptotic Shannon Theory
(seminar talk):
CAM/EE Seminar Series on Network Communications
and Information Processing, University of Notre Dame, Notre Dame, IN,
February 4, 2005
(Video,
Slides).

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