Research not for publishing papers, but for fun, for satisfying curiosity, and for revealing the truth.

This blog reports latest progresses in
(1) Signal Processing and Machine Learning for Biomedicine, Neuroimaging, Wearable Healthcare, and Smart-Home
(2) Sparse Signal Recovery and Compressed Sensing of Signals by Exploiting Spatiotemporal Structures
(3) My Works


Friday, February 3, 2012

Compressed Sensing Talks in ITA Workshop in San Diego (Sunday 2/5 - Friday 2/10)

From this Sunday we will have a great annual academic even in San Diego: ITA Workshop. Each year, the workshop invites many well-established scholars in the field of compressed sensing to give talks.

Here is the workshop calendar: http://ita.ucsd.edu/workshop/12/talks

Particularly, I found the following talks on compressed sensing/sparse signal recovery (I probably missed some):

Monday:
11:20: Quick partial sparse support recovery by Vincent Poor, Princeton, Ali Tajer, Princeton
3:00:  Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing by David Donoho, Stanford, Adel Javanmard, Stanford, Andrea Montanari, Stanford

Thursday (I missed some interesting talks in this day. More complete list can be seen here: http://marchonscience.blogspot.com/2012/02/compressed-sensing-talks-in-ita_09.html):
8:50: On L0 search for low-rank matrix completion, by Wei Dai, Imperial College London, Ely Kerman, UIUC, Olgica Milenkovic, UIUC
9:10: Orthogonal matching pursuit with replacement, by Inderjit Dhillon, University Of Texas, Prateek Jain, Microsoft, Ambuj Tewari, University Of Texas
3:00: Sparse sampling: bounds and applications by Martin Vetterli, EPFL
3:40: Compressive depth acquisition cameras: Principles and demonstrations by Vivek Goyal, MIT
4:15: Construction of low-coherence frames using group theory by Babak Hassibi, Caltech, Matthew Thill, Caltech
4:15: Bilinear generalized approximate message passing (BiG-AMP) for matrix recovery problems Phil Schniter, Ohio State, Volkan Cevher, EPFL
4:35: Sparse recovery with graph constraints by Meng Wang, Cornell, Weiyu Xu, Cornell, Enrique Mallada, Cornell, Kevin Tang, Cornell
4:55:  Asymptotic analysis of complex LASSO via complex approximate message passing by Arian Maleki, Rice, Laura Anitori, TNO, Netherlands, Zai Yang, Nanyang Technological University, Richard Baraniuk, Rice

Friday:
11:20: Faster algorithms for sparse fourier transform, by Haitham Hassanieh, MIT, Piotr Indyk, MIT, Dina Katabi, MIT, Eric Price, MIT
Compressive sensing meets group testing: LP decoding for non-linear (disjunctive) measurements, by Chun Lam Chan, CUHK, Sidharth Jaggi, CUHK, Venkatesh Saligrama, BU, Samar Agnihotri, CUHK
1:35: The Big Data bootstrap, by Ariel Kleiner, UC Berkeley, Ameet Talwalkar, UC Berkeley, Purna Sarkar, UC Berkeley, Michael Jordan, UC Berkeley

In addition to these talks, there are other interesting talks on high-dimensional data analysis, information theory, and neuroscience/AI.

Next week should be a wonderful week, except an unhappy thing: this year ITA will be hold in a hotel in San Diego, not in UCSD campus as previous years. It's so inconvenient :(

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