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SDM
2009
SIAM
123views Data Mining» more  SDM 2009»
15 years 11 months ago
Randomization Techniques for Graphs.
Mining graph data is an active research area. Several data mining methods and algorithms have been proposed to identify structures from graphs; still, the evaluation of those resu...
Gemma C. Garriga, Kai Puolamäki, Sami Hanhij&...
136
Voted
LICS
2010
IEEE
15 years 11 days ago
Fixed-Point Definability and Polynomial Time on Graphs with Excluded Minors
We prove that fixed-point logic with counting captures polynomial time on all classes of graphs with excluded minors. That is, for every class C of graphs such that some graph H is...
Martin Grohe
LATA
2009
Springer
15 years 9 months ago
Monadic Second-Order Logic for Graphs: Algorithmic and Language Theoretical Applications
This tutorial will present an overview of the use of Monadic Second-Order Logic to describe sets of finite graphs and graph transformations, in relation with the notions of tree-w...
Bruno Courcelle
132
Voted
ICML
2004
IEEE
16 years 3 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
334
Voted
ICA
2012
Springer
13 years 10 months ago
On Revealing Replicating Structures in Multiway Data: A Novel Tensor Decomposition Approach
A novel tensor decomposition called pattern or P-decomposition is proposed to make it possible to identify replicating structures in complex data, such as textures and patterns in ...
Anh Huy Phan, Andrzej Cichocki, Petr Tichavsk&yacu...