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» Learning from Highly Structured Data by Decomposition
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GLOBECOM
2010
IEEE
14 years 8 months ago
Cognitive Network Inference through Bayesian Network Analysis
Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios ...
Giorgio Quer, Hemanth Meenakshisundaram, Tamma Bhe...
ICMLA
2010
14 years 8 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
CPM
2004
Springer
144views Combinatorics» more  CPM 2004»
15 years 3 months ago
A Simple Optimal Representation for Balanced Parentheses
We consider succinct, or highly space-efficient, representations of a (static) string consisting of n pairs of balanced parentheses, that support natural operations such as findi...
Richard F. Geary, Naila Rahman, Rajeev Raman, Venk...
SAC
2009
ACM
15 years 4 months ago
Applying latent dirichlet allocation to group discovery in large graphs
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Keith Henderson, Tina Eliassi-Rad
NAR
2011
241views Computer Vision» more  NAR 2011»
14 years 4 months ago
PRIDB: a protein-RNA interface database
The Protein–RNA Interface Database (PRIDB) is a comprehensive database of protein–RNA interfaces extracted from complexes in the Protein Data Bank (PDB). It is designed to fac...
Benjamin A. Lewis, Rasna R. Walia, Michael Terribi...