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» Sparse random graphs with clustering
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ICPR
2002
IEEE
14 years 8 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
ECML
2004
Springer
14 years 28 days ago
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
Marco Saerens, François Fouss, Luh Yen, Pie...
CORR
2010
Springer
185views Education» more  CORR 2010»
13 years 7 months ago
Estimating and Sampling Graphs with Multidimensional Random Walks
Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
Bruno F. Ribeiro, Donald F. Towsley
PAMI
2006
141views more  PAMI 2006»
13 years 7 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee
WWW
2008
ACM
14 years 8 months ago
Graph theoretical framework for simultaneously integrating visual and textual features for efficient web image clustering
With the explosive growth of Web and the recent development in digital media technology, the number of images on the Web has grown tremendously. Consequently, Web image clustering...
Manjeet Rege, Ming Dong, Jing Hua