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» Notes on computing minimal approximant bases
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DSP
2006
13 years 10 months ago
Blind image deconvolution via dispersion minimization
In linear image restoration, the point spread function of the degrading system is assumed known even though this information is usually not available in real applications. As a re...
C. Vural, William A. Sethares
ECCV
2010
Springer
14 years 2 months ago
Practical Autocalibration
As it has been noted several times in literature, the difficult part of autocalibration efforts resides in the structural non-linearity of the search for the plane at infinity. I...
CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
14 years 1 months ago
Semidefinite programming methods for system realization and identification
We describe semidefinite programming methods for system realization and identification. For each of these two applications, a variant of a simple subspace algorithm is presented, i...
Zhang Liu, Lieven Vandenberghe
CDC
2008
IEEE
206views Control Systems» more  CDC 2008»
14 years 4 months ago
Approximate dynamic programming using support vector regression
— This paper presents a new approximate policy iteration algorithm based on support vector regression (SVR). It provides an overview of commonly used cost approximation architect...
Brett Bethke, Jonathan P. How, Asuman E. Ozdaglar
EMMCVPR
1999
Springer
14 years 2 months ago
A New Algorithm for Energy Minimization with Discontinuities
Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. These tasks can be formulated as energy minimization problems. In this paper, we conside...
Yuri Boykov, Olga Veksler, Ramin Zabih