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» Learning Generative Models with the Up-Propagation Algorithm
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GPEM
2002
95views more  GPEM 2002»
13 years 7 months ago
On Appropriate Adaptation Levels for the Learning of Gene Linkage
A number of algorithms have been proposed aimed at tackling the problem of learning "Gene Linkage" within the context of genetic optimisation, that is to say, the problem...
James Smith
FASE
2011
Springer
12 years 11 months ago
Automated Learning of Probabilistic Assumptions for Compositional Reasoning
Probabilistic verification techniques have been applied to the formal modelling and analysis of a wide range of systems, from communication protocols such as Bluetooth, to nanosca...
Lu Feng, Marta Z. Kwiatkowska, David Parker
ICML
2005
IEEE
14 years 8 months ago
Hierarchical Dirichlet model for document classification
The proliferation of text documents on the web as well as within institutions necessitates their convenient organization to enable efficient retrieval of information. Although tex...
Sriharsha Veeramachaneni, Diego Sona, Paolo Avesan...
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
12 years 3 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
ICA
2004
Springer
14 years 1 months ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela