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» On Conditions for Linearity of Optimal Estimation
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CVPR
2007
IEEE
15 years 11 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
14 years 10 months ago
Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
SIAMCO
2000
52views more  SIAMCO 2000»
14 years 9 months ago
Optimality of Energy Estimates for the Wave Equation with Nonlinear Boundary Velocity Feedbacks
We consider the wave equation damped by a nonlinear boundary velocity feedback q(ut). First we consider the case where q has a linear growth at infinity. We prove that the usual de...
Judith Vancostenoble, Patrick Martinez
INTERSPEECH
2010
14 years 4 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng
PAMI
2011
14 years 4 months ago
Rigid and Articulated Point Registration with Expectation Conditional Maximization
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...