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KDD
2007
ACM
124views Data Mining» more  KDD 2007»
13 years 10 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
GECCO
2009
Springer
159views Optimization» more  GECCO 2009»
13 years 9 months ago
Bayesian network structure learning using cooperative coevolution
We propose a cooperative-coevolution – Parisian trend – algorithm, IMPEA (Independence Model based Parisian EA), to the problem of Bayesian networks structure estimation. It i...
Olivier Barrière, Evelyne Lutton, Pierre-He...
JMLR
2008
188views more  JMLR 2008»
13 years 4 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
BMCBI
2010
155views more  BMCBI 2010»
13 years 4 months ago
A flexible R package for nonnegative matrix factorization
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
Renaud Gaujoux, Cathal Seoighe
IEEECIT
2010
IEEE
13 years 3 months ago
CFCSS without Aliasing for SPARC Architecture
With the increasing popularity of COTS (commercial off the shelf) components and multi-core processor in space and aviation applications, software fault tolerance becomes attracti...
Chao Wang, Zhongchuan Fu, Hongsong Chen, Wei Ba, B...