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Learning the Structure of Markov Logic Networks

Learning the Structure of Markov Logic Networks

Learning the Structure of Markov Logic Networks. Stanley Kok & Pedro Domingos Dept. of Computer Science and Eng. University of Washington. Overview. Motivation Background Structure Learning Algorithm Experiments Future Work & Conclusion. Motivation. Statistical Relational Learning (SRL)

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823 views • 60 slides
Discriminative Training of Markov Logic Networks

Discriminative Training of Markov Logic Networks

Discriminative Training of Markov Logic Networks. Parag Singla & Pedro Domingos. Outline. Motivation Review of MLNs Discriminative Training Experiments Link Prediction Object Identification Conclusion and Future Work. Outline. Motivation Review of MLNs Discriminative Training

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741 views • 58 slides
Discriminative Training of Markov Logic Networks

Discriminative Training of Markov Logic Networks

Discriminative Training of Markov Logic Networks. Parag Singla & Pedro Domingos. Outline. Motivation Review of MLNs Discriminative Training Experiments Link Prediction Object Identification Conclusion and Future Work. Outline. Motivation Review of MLNs Discriminative Training

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594 views • 58 slides
Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP. William Wang CMU ? UCSB. William Cohen CMU. Outline. Motivation/Background Logic Probability Combining logic and probabilities: Inference and semantics: MLNs Probabilistic DBs and the independent-tuple mechanism Recent research

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580 views • 57 slides
Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP. William Wang CMU ? UCSB. William Cohen CMU. Outline. Motivation/Background Logic Probability Combining logic and probabilities: Inference and semantics: MLNs Probabilistic DBs and the independent-tuple mechanism Recent research

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576 views • 57 slides
Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP

Scalable Statistical Relational Learning for NLP. William Wang CMU ? UCSB. William Cohen CMU. Outline. Motivation/Background Logic Probability Combining logic and probabilities: Inference and semantics: MLNs Probabilistic DBs and the independent-tuple mechanism Recent research

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596 views • 57 slides
Recursive Random Fields

Recursive Random Fields

Recursive Random Fields. Daniel Lowd University of Washington (Joint work with Pedro Domingos). One-Slide Summary. Question: How to represent uncertainty in relational domains? State-of-the-Art: Markov logic [Richardson & Domingos, 2004]

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360 views • 28 slides

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