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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
14 years 7 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
CVPR
2006
IEEE
15 years 11 months ago
Solving Markov Random Fields using Second Order Cone Programming Relaxations
This paper presents a generic method for solving Markov random fields (MRF) by formulating the problem of MAP estimation as 0-1 quadratic programming (QP). Though in general solvi...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
ECCV
2010
Springer
15 years 3 months ago
Graph Cut based Inference with Co-occurrence Statistics
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
ICCV
2007
IEEE
15 years 11 months ago
Capacity Scaling for Graph Cuts in Vision
Capacity scaling is a hierarchical approach to graph representation that can improve theoretical complexity and practical efficiency of max-flow/min-cut algorithms. Introduced by ...
Olivier Juan, Yuri Boykov
IDEAL
2007
Springer
15 years 3 months ago
PINCoC : A Co-clustering Based Approach to Analyze Protein-Protein Interaction Networks
A novel technique to search for functional modules in a protein-protein interaction network is presented. The network is represented by the adjacency matrix associated with the und...
Clara Pizzuti, Simona E. Rombo