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NIPS
1997
13 years 11 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
BCB
2010
213views Bioinformatics» more  BCB 2010»
13 years 4 months ago
Markov clustering of protein interaction networks with improved balance and scalability
Markov Clustering (MCL) is a popular algorithm for clustering networks in bioinformatics such as protein-protein interaction networks and protein similarity networks. An important...
Venu Satuluri, Srinivasan Parthasarathy, Duygu Uca...
ALENEX
2003
137views Algorithms» more  ALENEX 2003»
13 years 11 months ago
The Markov Chain Simulation Method for Generating Connected Power Law Random Graphs
Graph models for real-world complex networks such as the Internet, the WWW and biological networks are necessary for analytic and simulation-based studies of network protocols, al...
Christos Gkantsidis, Milena Mihail, Ellen W. Zegur...
MMMACNS
2005
Springer
14 years 3 months ago
Networks, Markov Lie Monoids, and Generalized Entropy
The continuous general linear group in n dimensions can be decomposed into two Lie groups: (1) an n(n-1) dimensional ‘Markov type’ Lie group that is defined by preserving the ...
Joseph E. Johnson
ICML
2007
IEEE
14 years 10 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney