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CIDM
2009
IEEE
14 years 2 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
14 years 7 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
EUROPAR
2009
Springer
14 years 2 days ago
Modelling Pilot-Job Applications on Production Grids
Pilot-job systems have emerged as a computation paradigm to cope with heterogeneity of production grids, greatly improving fault ratios and latency. Tools like DIANE, WISDOM-II, To...
Tristan Glatard, Sorina Camarasu-Pop
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 12 days ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
IJCNN
2007
IEEE
14 years 1 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...