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ICDCS
2002
IEEE
15 years 6 months ago
A Fully Distributed Framework for Cost-Sensitive Data Mining
Data mining systems aim to discover patterns and extract useful information from facts recorded in databases. A widely adopted approach is to apply machine learning algorithms to ...
Wei Fan, Haixun Wang, Philip S. Yu, Salvatore J. S...
DAGSTUHL
1990
15 years 2 months ago
Parallel Distributed Belief Networks
A parallel distributed computational model for reasoning and learning is discussed based on a belief network paradigm. Issues like reasoning and learning for the proposed model ar...
Wilson X. Wen
ITICSE
2004
ACM
15 years 6 months ago
Evaluating the effectiveness of ICT to support globally distributed PBL teams
In the 21st century it is becoming increasingly common to work and learn in teams that are globally distributed. Such teams rely heavily on ICT to facilitate communication. There ...
Chew Swee Cheng, Chris Beaumont
ML
2012
ACM
385views Machine Learning» more  ML 2012»
13 years 9 months ago
An alternative view of variational Bayes and asymptotic approximations of free energy
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
Kazuho Watanabe
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
15 years 7 months ago
Factorial representations to generate arbitrary search distributions
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
Marc Toussaint