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» Generating maximal models using the stable model semantics
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EACL
2006
ACL Anthology
15 years 5 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 8 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 5 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 2 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 4 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