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AMAI
2004
Springer
16 years 3 days ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
KDD
2010
ACM
250views Data Mining» more  KDD 2010»
15 years 8 months ago
On community outliers and their efficient detection in information networks
Linked or networked data are ubiquitous in many applications. Examples include web data or hypertext documents connected via hyperlinks, social networks or user profiles connected...
Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Su...
BMCBI
2010
139views more  BMCBI 2010»
15 years 6 months ago
A highly efficient multi-core algorithm for clustering extremely large datasets
Background: In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput t...
Johann M. Kraus, Hans A. Kestler
ICDCS
2008
IEEE
16 years 1 months ago
Correlation-Aware Object Placement for Multi-Object Operations
A multi-object operation incurs communication or synchronization overhead when the requested objects are distributed over different nodes. The object pair correlations (the probab...
Ming Zhong, Kai Shen, Joel I. Seiferas
PAMI
2008
145views more  PAMI 2008»
15 years 6 months ago
Latent-Space Variational Bayes
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...
JaeMo Sung, Zoubin Ghahramani, Sung Yang Bang