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Ubiquitously Supervised Subspace Learning

IEEE Transactions on Image Processing, 2009
In this paper, our contributions to the subspace learning problem are two-fold. We first justify that most popular subspace learning algorithms, unsupervised or supervised, can be unitedly explained as instances of a ubiquitously supervised prototype. They all essentially minimize the intraclass compactness and at the same time maximize the interclass ...
Yang, J., Yan, S., Huang, T.S.
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Semi-Supervised Learning

2005
For many classification problems, unlabeled training data are inexpensive and readily available, whereas labeling training data imposes costs. Semi-supervised classification algorithms aim at utilizing information contained in unlabeled data in addition to the (few) labeled data.
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Learning with Partial Supervision

2009
Recently the field of machine learning, pattern recognition, and data mining has witnessed a new research stream that is <i>learning with partial supervisio</i>n -LPS- (known also as <i>semi-supervised learning</i>). This learning scheme is motivated by the fact that the process of acquiring the labeling information of data ...
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Supervised Learning

2003
Publisher Summary In modern times, the task of organizing knowledge into systematic structures is studied by ontologists and library scientists, resulting in such well-known structures as the Dewey decimal system, the Library of Congress catalog, the AlMS Mathematics Subject Classification, and the U.S. Patent Office subject classification.
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Supervised Learning

2022
S. Sumathi   +3 more
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Learning in supervision

2018
Erik de Haan, Willemine Regouin
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Supervised Learning

2017
Laura Igual, Santi SeguĂ­
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Supervised Learning

2009
Jong Kyoung Kim   +2 more
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