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» Community Learning by Graph Approximation
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CVPR
2011
IEEE
14 years 6 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
14 years 11 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»
15 years 3 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
14 years 4 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
15 years 4 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