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» Learning the Common Structure of Data
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UAI
2003
15 years 5 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
IJDST
2011
117views more  IJDST 2011»
14 years 7 months ago
Integrating Production Automation Expert Knowledge Across Engineering Domains
The engineering of complex production automation systems involves experts from several backgrounds, such as mechanical, electrical, and software engineering. The production automa...
Thomas Moser, Stefan Biffl, Wikan Danar Sunindyo, ...
121
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BMCBI
2008
103views more  BMCBI 2008»
15 years 3 months ago
Parameter estimation for robust HMM analysis of ChIP-chip data
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Peter Humburg, David Bulger, Glenn Stone
NIPS
2008
15 years 5 months ago
Exact Convex Confidence-Weighted Learning
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Koby Crammer, Mark Dredze, Fernando Pereira
137
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ICANN
2009
Springer
15 years 10 months ago
Learning Features by Contrasting Natural Images with Noise
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...
Michael Gutmann, Aapo Hyvärinen