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» Community Learning by Graph Approximation
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CVPR
2011
IEEE
13 years 3 months ago
Nonparametric Density Estimation on A Graph: Learning Framework, Fast Approximation and Application in Image Segmentation
We present a novel framework for tree-structure embedded density estimation and its fast approximation for mode seeking. The proposed method could find diverse applications in co...
Zhiding Yu, Oscar Au, Ketan Tang
ESANN
2007
13 years 9 months ago
Causality and communities in neural networks
A recently proposed nonlinear extension of Granger causality is used to map the dynamics of a neural population onto a graph, whose community structure characterizes the collective...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...
SYNASC
2006
IEEE
106views Algorithms» more  SYNASC 2006»
14 years 1 months ago
A Quality Measure for Multi-Level Community Structure
Mining relational data often boils down to computing clusters, that is finding sub-communities of data elements forming cohesive sub-units, while being well separated from one an...
Maylis Delest, Jean-Marc Fedou, Guy Melanço...
COMBINATORICA
2010
13 years 2 months ago
Approximation algorithms via contraction decomposition
We prove that the edges of every graph of bounded (Euler) genus can be partitioned into any prescribed number k of pieces such that contracting any piece results in a graph of bou...
Erik D. Demaine, MohammadTaghi Hajiaghayi, Bojan M...
WWW
2010
ACM
14 years 2 months ago
Empirical comparison of algorithms for network community detection
Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest. In practice, one typically chooses...
Jure Leskovec, Kevin J. Lang, Michael W. Mahoney