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» Approximate Inference and Constrained Optimization
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BMCBI
2007
197views more  BMCBI 2007»
13 years 7 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
ICMLA
2008
13 years 9 months ago
Probabilistic Exploitation of the Lucas and Kanade Smoothness Constraint
The basic idea of Lucas and Kanade is to constrain the local motion measurement by assuming a constant velocity within a spatial neighborhood. We reformulate this spatial constrai...
Volker Willert, Julian Eggert, Marc Toussaint, Edg...
NIPS
2008
13 years 9 months ago
Syntactic Topic Models
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Jordan L. Boyd-Graber, David M. Blei
CVPR
2009
IEEE
15 years 2 months ago
Alphabet SOUP: A Framework for Approximate Energy Minimization
Many problems in computer vision can be modeled using conditional Markov random fields (CRF). Since finding the maximum a posteriori (MAP) solution in such models is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
ICRA
2010
IEEE
99views Robotics» more  ICRA 2010»
13 years 6 months ago
Retraction-based RRT planner for articulated models
— We present a new retraction algorithm for high DOF articulated models and use our algorithm to improve the performance of RRT planners in narrow passages. The retraction step i...
Jia Pan, Liangjun Zhang, Dinesh Manocha