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» Learning Word Representations from Relational Graphs
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NIPS
2001
15 years 5 months ago
Grammatical Bigrams
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...
Mark A. Paskin
143
Voted
ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 3 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
237
Voted
SIGLEX
1991
15 years 7 months ago
Logical Structures in the Lexicon
The lexical entry for a word must contain all the information needed to construct a semantic representation for sentences that contain the word. Because of that requirement, the f...
John F. Sowa
172
Voted
FCSC
2010
238views more  FCSC 2010»
15 years 1 months ago
Knowledge discovery through directed probabilistic topic models: a survey
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad
ACL
1996
15 years 5 months ago
Linguistic Structure as Composition and Perturbation
This paper discusses the problem of learning language from unprocessed text and speech signals, concentrating on the problem of learning a lexicon. In particular, it argues for a ...
Carl de Marcken