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SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
13 years 11 months ago
Fast Multilevel Transduction on Graphs
The recent years have witnessed a surge of interest in graphbased semi-supervised learning methods. The common denominator of these methods is that the data are represented by the...
Fei Wang, Changshui Zhang
SDM
2004
SIAM
194views Data Mining» more  SDM 2004»
13 years 11 months ago
Finding Frequent Patterns in a Large Sparse Graph
Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteri...
Michihiro Kuramochi, George Karypis
ICDM
2010
IEEE
105views Data Mining» more  ICDM 2010»
13 years 8 months ago
On the Vulnerability of Large Graphs
Given a large graph, like a computer network, which k nodes should we immunize (or monitor, or remove), to make it as robust as possible against a computer virus attack? We need (...
Hanghang Tong, B. Aditya Prakash, Charalampos E. T...
PAKDD
2011
ACM
209views Data Mining» more  PAKDD 2011»
13 years 1 months ago
Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation
Abstract. Given a graph with billions of nodes and edges, how can we find patterns and anomalies? Are there nodes that participate in too many or too few triangles? Are there clos...
U. Kang, Brendan Meeder, Christos Faloutsos
SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
13 years 11 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee