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» On Generating Random Network Structures: Connected Graphs
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110
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BMCBI
2010
147views more  BMCBI 2010»
15 years 20 days ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
JMLR
2010
165views more  JMLR 2010»
14 years 7 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
APVIS
2006
15 years 1 months ago
Visual analysis of network centralities
Centrality analysis determines the importance of vertices in a network based on their connectivity within the network structure. It is a widely used technique to analyse network-s...
Tim Dwyer, Seok-Hee Hong, Dirk Koschützki, Fa...
114
Voted
ICDAR
2009
IEEE
14 years 10 months ago
Learning Bayesian Networks by Evolution for Classifier Combination
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...
Claudio De Stefano, Francesco Fontanella, Alessand...
100
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PADS
2005
ACM
15 years 6 months ago
Software Diversity as a Defense against Viral Propagation: Models and Simulations
The use of software diversity has often been discussed in the research literature as an effective means to break up the software monoculture present on the Internet and to thus p...
Adam J. O'Donnell, Harish Sethu