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Markov logic network

Known as: MLN (disambiguation), Markov logic, Markov logic networks 
A Markov logic network (MLN) is a probabilistic logic which applies the ideas of a Markov network to first-order logic, enabling uncertain inference… 
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Related topics

Related topics

19 relations
Atomic formulaBelief propagationClique (graph theory)Constrained conditional model

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Structure Learning for Markov Logic Networks
Most existing learning methods for Markov Logic Networks (MLNs) use batch training, which becomes computationally expensive and… 
2017
2017
Ensemble method to joint inference for knowledge extraction
2016
2016
A Learning Algorithm for Relational Logistic Regression: Preliminary Results
Relational logistic regression (RLR) is a representation of conditional probability in terms of weighted formulae for modelling… 
2012
2012
Using First-Order Logic to Compress Sentences
Sentence compression is one of the most challenging tasks in natural language processing,which may be of increasing interest… 
2011
2011
Research on Markov Logic Networks
Markov logic networks(MLNs) is a statistical relational learning(SRL) model,which combines Markov network and first order logic… 
2010
2010
Relational Learning for Collective Classification of Entities in Images
We consider the problem of discrete multi-label entity classification in images. We argue that the framework of Markov Logic can… 
2010
2010
Structure learning in markov logic networks
Markov logic networks (MLNs) [86, 24] are a powerful representation combining first-order logic and probability. An MLN attaches… 
2009
2009
Integrating Logic and Probability: Algorithmic Improvements in Markov Logic Networks
This dissertation proposes novel algorithms for learning and inference in Markov Logic Networks. Statistical Relational Learning… 
Review
2007
Review
2007
Survey of Markov Logic Networks
Statistical Relational Learning(SRL) is a highlight in AI research field,and has important applications on many areas,such as… 
2003
2003
Coverage-Optimized Retrieval
We present a generalization of similarity-based retrieval in recommender systems which ensures that for any case that is… 
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