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182
Voted
ICML
2009
IEEE
16 years 7 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
193
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ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
177
Voted
SDM
2009
SIAM
16 years 4 months ago
2009
SIAM
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
200
Voted
DAGM
2009
Springer
16 years 1 months ago
2009
Springer
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
196
Voted
MM
2004
ACM
16 years 9 days ago
2004
ACM
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...