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03513nam a2200529 4500 |
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978-3-030-00734-8 |
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DE-He213 |
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20191028132246.0 |
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181206s2019 gw | s |||| 0|eng d |
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|a 9783030007348
|9 978-3-030-00734-8
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|a 10.1007/978-3-030-00734-8
|2 doi
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|d GrThAP
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|a QA76.9.D343
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|a UNF
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|a COM021030
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|a 006.312
|2 23
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|a Ding, Zhengming.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Learning Representation for Multi-View Data Analysis
|h [electronic resource] :
|b Models and Applications /
|c by Zhengming Ding, Handong Zhao, Yun Fu.
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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|a X, 268 p. 76 illus., 69 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Advanced Information and Knowledge Processing,
|x 1610-3947
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|a Introduction -- Multi-view Clustering with Complete Information -- Multi-view Clustering with Partial Information -- Multi-view Outlier Detection -- Multi-view Transformation Learning -- Zero-Shot Learning -- Missing Modality Transfer Learning -- Deep Domain Adaptation -- Deep Domain Generalization. .
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|a This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers' understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.
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|a Data mining.
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|a Artificial intelligence.
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|a Pattern recognition.
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|a Data Mining and Knowledge Discovery.
|0 http://scigraph.springernature.com/things/product-market-codes/I18030
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Pattern Recognition.
|0 http://scigraph.springernature.com/things/product-market-codes/I2203X
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700 |
1 |
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|a Zhao, Handong.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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700 |
1 |
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|a Fu, Yun.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a SpringerLink (Online service)
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773 |
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783030007331
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|i Printed edition:
|z 9783030007355
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830 |
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|a Advanced Information and Knowledge Processing,
|x 1610-3947
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856 |
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|u https://doi.org/10.1007/978-3-030-00734-8
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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|a Computer Science (Springer-11645)
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