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» Generating maximal models using the stable model semantics
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EACL
2006
ACL Anthology
15 years 7 months ago
Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Ayman Farahat, Francine Chen
MMM
2011
Springer
368views Multimedia» more  MMM 2011»
14 years 10 months ago
Correlated PLSA for Image Clustering
Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independen...
Peng Li, Jian Cheng, Zechao Li, Hanqing Lu
DAC
2002
ACM
16 years 7 months ago
Guaranteed passive balancing transformations for model order reduction
The major concerns in state-of-the-art model reduction algorithms are: achieving accurate models of sufficiently small size, numerically stable and efficient generation of the mod...
Joel R. Phillips, Luca Daniel, Luis Miguel Silveir...
ICST
2010
IEEE
15 years 5 months ago
Timed Moore Automata: Test Data Generation and Model Checking
Abstract—In this paper we introduce Timed Moore Automata, a specification formalism which is used in industrial train control applications for specifying the real-time behavior ...
Helge Löding, Jan Peleska
COGSCI
2002
108views more  COGSCI 2002»
15 years 6 months ago
Statistical models for the induction and use of selectional preferences
Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach ...
Marc Light, Warren R. Greiff