This paper surveys recent work in applying ideas from graphical models and message passing algorithms to solve large scale regularized regression problems. In particular, the focu...
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
We study the problem of distributed sampling and compression in sensor networks when the sensors are digital cameras that acquire a 3-D visual scene of interest from different vie...
3D MRI of the upper airway has provided valuable insights into vocal tract shaping and data for the modeling of speech production. Small movements of articulators can lead to larg...
Yoon-Chul Kim, Shrikanth S. Narayanan, Krishna S. ...