1. Markov Logic

    Pedro Domingos1 , Stanley Kok1 , Daniel Lowd1 , Hoifung Poon1, Matthew Richardson2, and Parag Singla1 Department of Computer Science and Engineering University of Washington Seattle, WA 98195-2350, U.S.A. {pedrod, koks, lowd, hoifung, parag}@cs.washington.edu 2 Microsoft Research Redmond, WA 98052 mattri@microsoft.com 1 Abstract. Most real-world machine learning problems have both statistical and relational aspects. Thus learners need representations that combine probability and re
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
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