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CVPR
2011
IEEE
14 years 9 months ago
Blind Deconvolution Using A Normalized Sparsity Measure
Blind image deconvolution is an ill-posed problem that requires regularization to solve. However, many common forms of image prior used in this setting have a major drawback in th...
Dilip Krishnan, Rob Fergus
127
Voted
SIAMSC
2011
162views more  SIAMSC 2011»
14 years 8 months ago
Accelerating the LSTRS Algorithm
In a recent paper [Rojas, Santos, Sorensen: ACM ToMS 34 (2008), Article 11] an efficient method for solving the Large-Scale Trust-Region Subproblem was suggested which is based on ...
Jörg Lampe, Marielba Rojas, Danny C. Sorensen...
142
Voted
EJASP
2010
133views more  EJASP 2010»
14 years 8 months ago
Improving Density Estimation by Incorporating Spatial Information
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
Laura M. Smith, Matthew S. Keegan, Todd Wittman, G...
146
Voted
ICASSP
2011
IEEE
14 years 5 months ago
Source localization using time difference of arrival within a sparse representation framework
The problem addressed is source localization via time-differenceof-arrival estimation in a multipath channel. Solving this localization problem typically implies cross-correlating...
Ciprian R. Comsa, Alexander M. Haimovich, Stuart C...
131
Voted
CSDA
2011
14 years 8 months ago
Hierarchical multilinear models for multiway data
Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as produc...
Peter D. Hoff