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» Classification of unlabeled point sets using ANSIG
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TNN
2010
154views Management» more  TNN 2010»
14 years 6 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
IGARSS
2009
14 years 9 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
CVPR
2011
IEEE
14 years 3 months ago
Max-margin Clustering: Detecting Margins from Projections of Points on Lines
Given a unlabelled set of points X ∈ RN belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We...
Raghuraman Gopalan, Jagan Sankaranarayanan
DASFAA
2008
IEEE
120views Database» more  DASFAA 2008»
15 years 6 months ago
Knowledge Transferring Via Implicit Link Analysis
In this paper, we design a local classification algorithm using implicit link analysis, considering the situation that the labeled and unlabeled data are drawn from two different ...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Yong Yu
85
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FLAIRS
2004
15 years 1 months ago
Automatic Generation of Background Text to Aid Classification
We illustrate that Web searches can often be utilized to generate background text for use with text classification. This is the case because there are frequently many pages on the...
Sarah Zelikovitz, Robert Hafner