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» Factorial Learning and the EM Algorithm
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ICMLA
2009
13 years 5 months ago
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapu...
ICML
2003
IEEE
14 years 8 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
NIPS
2008
13 years 9 months ago
Integrating Locally Learned Causal Structures with Overlapping Variables
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
Robert E. Tillman, David Danks, Clark Glymour
GBRPR
2007
Springer
13 years 11 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...
ICIAP
2001
Springer
14 years 7 months ago
Recognition of Shape-Changing Hand Gestures Based on Switching Linear Model
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...