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ICML
2007
IEEE
15 years 10 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
86
Voted
PR
2008
206views more  PR 2008»
14 years 9 months ago
A study of graph spectra for comparing graphs and trees
The spectrum of a graph has been widely used in graph theory to characterise the properties of a graph and extract information from its structure. It has also been employed as a g...
Richard C. Wilson, Ping Zhu
SODA
2010
ACM
177views Algorithms» more  SODA 2010»
15 years 7 months ago
Convergence, Stability, and Discrete Approximation of Laplace Spectra
Spectral methods have been widely used in a broad range of application fields. One important object involved in such methods is the Laplace-Beltrami operator of a manifold. Indeed...
Tamal K. Dey, Pawas Ranjan, Yusu Wang
81
Voted
CVPR
2008
IEEE
15 years 11 months ago
Manifold learning using robust Graph Laplacian for interactive image search
Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in partially labeling a ...
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert...
109
Voted
TIP
2010
155views more  TIP 2010»
14 years 8 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He