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» Graph Based Semi-supervised Learning with Sharper Edges
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ICPR
2008
IEEE
14 years 9 months ago
Image retrieval with graph kernel on regions
In the framework of the interactive search in image databases, we are interested in similarity measures able to learn during the search and usable in real-time. Images are represe...
Justine Lebrun, Sylvie Philipp-Foliguet, Philippe ...
CVPR
2007
IEEE
14 years 10 months ago
Image Classification with Segmentation Graph Kernels
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
Francis Bach, Zaïd Harchaoui
CORR
2008
Springer
116views Education» more  CORR 2008»
13 years 8 months ago
Learning to rank with combinatorial Hodge theory
Abstract. We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced -- characteristics that are almost universal to modern dat...
Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
14 years 2 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
13 years 9 months ago
Semi-supervised Multi-label Learning by Solving a Sylvester Equation
Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-labe...
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang