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CONTEXT
2007
Springer
15 years 4 months ago
OCCAM: Ontology-Based Computational Contextual Analysis and Modeling
The ability to model cognitive agents depends crucially on being able to encode and infer with contextual information at many levels (such as situational, psychological, social, or...
Srini Narayanan, Katie Sievers, Steven J. Maiorano
ICIP
2004
IEEE
15 years 11 months ago
Estimation of mixtures of probabilistic pca with stochastic em for the 3d biplanar reconstruction of scoliotic rib cage
In this paper, we present a robust method for estimating the model parameters in a mixture of probabilistic principal component analyzers. This method is based on the Stochastic v...
François Destrempes, Jacques A. de Guise, M...
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
15 years 10 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
FORMATS
2003
Springer
15 years 3 months ago
Performance Analysis of Probabilistic Timed Automata Using Digital Clocks
Probabilistic timed automata, a variant of timed automata extended with discrete probability distributions, is a specification formalism suitable for describing both nondeterminis...
Marta Z. Kwiatkowska, Gethin Norman, David Parker,...
CONCUR
2009
Springer
15 years 4 months ago
Partial Order Reduction for Probabilistic Systems: A Revision for Distributed Schedulers
Abstract. The technique of partial order reduction (POR) for probabilistic model checking prunes the state space of the model so that a maximizing scheduler and a minimizing one pe...
Sergio Giro, Pedro R. D'Argenio, Luis María...