COPYRIGHT YEAR

2017

AUTHORS

Xiaojuan Ban, Michele Mukeshimana, Nelson Karani

TITLE

Sparse Extreme Learning Machine Using Privileged Information for Classification

ABSTRACT

In human learning process, teachers play an important role of transferring knowledge and providing some additional information for better understanding. In machine learning, the role of the teacher has been mostly ignored. Introduction of a new learning paradigm named Learning Using Privileged Information (LUPI) includes the elements of human teaching in machine learning. This paper proposes a learning method using privileged information based on a Sparse Extreme Learning Machine (ELM). Our method aims to improve the classification performance by reducing the testing error. Experimental results show improvements in training accuracy and testing error reduction over the classical methods in classification.

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26 TRIPLES      24 PREDICATES      23 URIs      13 LITERALS

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2 sg:abstractRights OpenAccess
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6 sg:copyrightHolder Springer Nature Singapore Pte Ltd.
7 sg:copyrightYear 2017
8 sg:ddsId Chap23
9 sg:doi 10.1007/978-981-10-5230-9_23
10 sg:esmRights OpenAccess
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16 sg:language En
17 sg:license http://scigraph.springernature.com/explorer/license/
18 sg:metadataRights OpenAccess
19 sg:pageFirst 205
20 sg:pageLast 213
21 sg:scigraphId 1b7c610d771f19315ce49229565cd262
22 sg:title Sparse Extreme Learning Machine Using Privileged Information for Classification
23 sg:webpage https://link.springer.com/10.1007/978-981-10-5230-9_23
24 rdf:type sg:BookChapter
25 rdfs:label BookChapter: Sparse Extreme Learning Machine Using Privileged Information for Classification
26 owl:sameAs http://lod.springer.com/data/bookchapter/978-981-10-5230-9_23
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