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» Max-Margin Weight Learning for Markov Logic Networks
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CVPR
2008
IEEE
14 years 7 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
ICML
2007
IEEE
14 years 5 months ago
Comparisons of sequence labeling algorithms and extensions
In this paper, we survey the current state-ofart models for structured learning problems, including Hidden Markov Model (HMM), Conditional Random Fields (CRF), Averaged Perceptron...
Nam Nguyen, Yunsong Guo
ICMLA
2010
13 years 2 months ago
Heuristic Method for Discriminative Structure Learning of Markov Logic Networks
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
Quang-Thang Dinh, Matthieu Exbrayat, Christel Vrai...
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 4 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ICML
2005
IEEE
14 years 5 months ago
Learning the structure of Markov logic networks
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. In this pap...
Stanley Kok, Pedro Domingos