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» Improving Shape Retrieval by Learning Graph Transduction
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JMLR
2008
139views more  JMLR 2008»
14 years 9 months ago
Regularization on Graphs with Function-adapted Diffusion Processes
Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman
ICML
2008
IEEE
15 years 10 months ago
Graph transduction via alternating minimization
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
Jun Wang, Tony Jebara, Shih-Fu Chang
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
14 years 7 months ago
Graph Regularized Transductive Classification on Heterogeneous Information Networks
A heterogeneous information network is a network composed of multiple types of objects and links. Recently, it has been recognized that strongly-typed heterogeneous information net...
Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han...
MM
2005
ACM
134views Multimedia» more  MM 2005»
15 years 3 months ago
Graph based multi-modality learning
To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point ...
Hanghang Tong, Jingrui He, Mingjing Li, Changshui ...
SIGIR
2008
ACM
14 years 9 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff