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» Approximate data mining in very large relational data
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ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
15 years 8 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
ICDM
2008
IEEE
102views Data Mining» more  ICDM 2008»
15 years 8 months ago
A Non-parametric Semi-supervised Discretization Method
Semi-supervised classification methods aim to exploit labelled and unlabelled examples to train a predictive model. Most of these approaches make assumptions on the distribution ...
Alexis Bondu, Marc Boullé, Vincent Lemaire,...
IGARSS
2009
14 years 11 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
TIP
2010
145views more  TIP 2010»
14 years 8 months ago
Joint Manifolds for Data Fusion
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...
Mark A. Davenport, Chinmay Hegde, Marco F. Duarte,...
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
15 years 8 months ago
Knowledge Discovery from Citation Networks
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Y...