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FUIN
2008
108views more  FUIN 2008»
13 years 7 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
ECCV
2004
Springer
14 years 10 months ago
A Constrained Semi-supervised Learning Approach to Data Association
Data association (obtaining correspondences) is a ubiquitous problem in computer vision. It appears when matching image features across multiple images, matching image features to ...
Hendrik Kück, Nando de Freitas, Peter Carbone...
CVPR
2000
IEEE
14 years 11 months ago
Order Parameters for Minimax Entropy Distributions: When Does High Level Knowledge Help?
Many problems in vision can be formulated as Bayesian inference. It is important to determine the accuracy of these inferences and how they depend on the problem domain. In recent...
Alan L. Yuille, James M. Coughlan, Song Chun Zhu, ...
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
13 years 12 days ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
PAMI
2007
187views more  PAMI 2007»
13 years 8 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...