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» Linear analysis of random process variability
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UAI
2004
13 years 8 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper
ISPW
2007
IEEE
14 years 1 months ago
Project Delay Variability Simulation in Software Product Line Development
The possible variability of project delay is useful information to understand and mitigate the project delay risk. However, it is not sufficiently considered in the literature con...
Makoto Nonaka, Liming Zhu, Muhammad Ali Babar, Mar...
JMLR
2006
125views more  JMLR 2006»
13 years 7 months ago
A Linear Non-Gaussian Acyclic Model for Causal Discovery
In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data. Such methods make various assumptions on the data generating ...
Shohei Shimizu, Patrik O. Hoyer, Aapo Hyvärin...
BMCBI
2008
58views more  BMCBI 2008»
13 years 7 months ago
Recovering probabilities for nucleotide trimming processes for T cell receptor TRA and TRG V-J junctions analyzed with IMGT tool
Background: Nucleotides are trimmed from the ends of variable (V), diversity (D) and joining (J) genes during immunoglobulin (IG) and T cell receptor (TR) rearrangements in B cell...
Kevin Bleakley, Marie-Paule Lefranc, Gérard...
NN
2000
Springer
177views Neural Networks» more  NN 2000»
13 years 7 months ago
Independent component analysis: algorithms and applications
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
Aapo Hyvärinen, Erkki Oja