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NIPS
1997
15 years 1 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»
14 years 6 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»
15 years 1 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
15 years 5 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
16 years 17 days 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