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» Church: a language for generative models
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AIRS
2009
Springer
16 years 29 days ago
A Latent Dirichlet Framework for Relevance Modeling
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
Viet Ha-Thuc, Padmini Srinivasan
FOAL
2009
ACM
16 years 26 days ago
A machine-checked model of safe composition
Programs of a software product line can be synthesized by composing features which implement some unit of program functionality. In most product lines, only some combination of fe...
Benjamin Delaware, William R. Cook, Don S. Batory
WOSP
2004
ACM
15 years 11 months ago
Performance modeling from software components
When software products are assembled from pre-defined components, performance prediction should be based on the components also. This supports rapid model-building, using previous...
Xiuping Wu, C. Murray Woodside
KI
2007
Springer
16 years 15 days ago
Extending Markov Logic to Model Probability Distributions in Relational Domains
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
Dominik Jain, Bernhard Kirchlechner, Michael Beetz
ACL
1993
15 years 7 months ago
Towards History-Based Grammars: Using Richer Models for Probabilistic Parsing
We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...