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» A General Framework for Graph Sparsification
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ICML
2007
IEEE
14 years 8 months ago
Learning random walks to rank nodes in graphs
Ranking nodes in graphs is of much recent interest. Edges, via the graph Laplacian, are used to encourage local smoothness of node scores in SVM-like formulations with generalizat...
Alekh Agarwal, Soumen Chakrabarti
BMCBI
2008
115views more  BMCBI 2008»
13 years 7 months ago
BioGraphE: high-performance bionetwork analysis using the Biological Graph Environment
Background: Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching h...
George Chin Jr., Daniel G. Chavarría-Mirand...
SIGMOD
2005
ACM
136views Database» more  SIGMOD 2005»
14 years 1 months ago
Optimizing recursive queries in SQL
Recursion represents an important addition to the SQL language. This work focuses on the optimization of linear requeries in SQL. To provide an abstract framework for discussion, ...
Carlos Ordonez
IBPRIA
2003
Springer
14 years 27 days ago
Segmentation of Curvilinear Objects Using a~Watershed-Based Curve Adjacency Graph
Abstract. This paper presents a general framework to segment curvilinear objects in 2D images. A pre-processing step relies on mathematical morphology to obtain a connected line wh...
Thierry Géraud
ECCV
2010
Springer
13 years 8 months ago
Nonlocal Multiscale Hierarchical Decomposition on Graphs
Abstract. The decomposition of images into their meaningful components is one of the major tasks in computer vision. Tadmor, Nezzar and Vese [1] have proposed a general approach fo...
Moncef Hidane, Olivier Lezoray, Vinh-Thong Ta, Abd...