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UAI
1996
15 years 5 months ago
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
David Maxwell Chickering, David Heckerman
BRAIN
2010
Springer
15 years 5 months ago
Cognitive Informatics and Denotational Mathematical Means for Brain Informatics
Cognitive informatics studies the natural intelligence and the brain from a theoretical and a computational approach, which rigorously explains the ms of the brain by a fundamental...
Yingxu Wang
DAGM
2010
Springer
15 years 5 months ago
Random Fourier Approximations for Skewed Multiplicative Histogram Kernels
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
Fuxin Li, Catalin Ionescu, Cristian Sminchisescu
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
15 years 4 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
CGF
2008
192views more  CGF 2008»
15 years 4 months ago
Non-Rigid Registration Under Isometric Deformations
We present a robust and efficient algorithm for the pairwise non-rigid registration of partially overlapping 3D surfaces. Our approach treats non-rigid registration as an optimiza...
Qi-Xing Huang, Bart Adams, Martin Wicke, Leonidas ...
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