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» Improved learning of Bayesian networks
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AI
2008
Springer
13 years 6 months ago
MEBN: A language for first-order Bayesian knowledge bases
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...
Kathryn B. Laskey
ICML
2008
IEEE
14 years 8 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
PAMI
2010
188views more  PAMI 2010»
13 years 6 months ago
A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding
—Facial expression is a natural and powerful means of human communication. Recognizing spontaneous facial actions, however, is very challenging due to subtle facial deformation, ...
Yan Tong, Jixu Chen, Qiang Ji
AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
14 years 21 days ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...