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Showing 1 - 6 of
6 matches in All Departments
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Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part V (Paperback, 1st ed. 2020)
Hai-Qin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, …
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R3,140
Discovery Miles 31 400
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Ships in 10 - 15 working days
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The two-volume set CCIS 1332 and 1333 constitutes thoroughly
refereed contributions presented at the 27th International
Conference on Neural Information Processing, ICONIP 2020, held in
Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378
papers was carefully reviewed and selected for publication out of
618 submissions. The 191 papers included in this volume set were
organized in topical sections as follows: data mining; healthcare
analytics-improving healthcare outcomes using big data analytics;
human activity recognition; image processing and computer vision;
natural language processing; recommender systems; the 13th
international workshop on artificial intelligence and
cybersecurity; computational intelligence; machine learning; neural
network models; robotics and control; and time series analysis. *
The conference was held virtually due to the COVID-19 pandemic.
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Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 18-22, 2020, Proceedings, Part IV (Paperback, 1st ed. 2020)
Hai-Qin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, …
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R3,140
Discovery Miles 31 400
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Ships in 10 - 15 working days
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The two-volume set CCIS 1332 and 1333 constitutes thoroughly
refereed contributions presented at the 27th International
Conference on Neural Information Processing, ICONIP 2020, held in
Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378
papers was carefully reviewed and selected for publication out of
618 submissions. The 191 papers included in this volume set were
organized in topical sections as follows: data mining; healthcare
analytics-improving healthcare outcomes using big data analytics;
human activity recognition; image processing and computer vision;
natural language processing; recommender systems; the 13th
international workshop on artificial intelligence and
cybersecurity; computational intelligence; machine learning; neural
network models; robotics and control; and time series analysis. *
The conference was held virtually due to the COVID-19 pandemic.
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Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part II (Paperback, 1st ed. 2020)
Hai-Qin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, …
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R3,133
Discovery Miles 31 330
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Ships in 10 - 15 working days
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The three-volume set of LNCS 12532, 12533, and 12534 constitutes
the proceedings of the 27th International Conference on Neural
Information Processing, ICONIP 2020, held in Bangkok, Thailand, in
November 2020. Due to COVID-19 pandemic the conference was held
virtually. The 187 full papers presented were carefully reviewed
and selected from 618 submissions. The papers address the emerging
topics of theoretical research, empirical studies, and applications
of neural information processing techniques across different
domains. The second volume, LNCS 12533, is organized in topical
sections on computational intelligence; machine learning; robotics
and control.
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Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part III (Paperback, 1st ed. 2020)
Hai-Qin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, …
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R3,076
Discovery Miles 30 760
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Ships in 10 - 15 working days
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The three-volume set of LNCS 12532, 12533, and 12534 constitutes
the proceedings of the 27th International Conference on Neural
Information Processing, ICONIP 2020, held in Bangkok, Thailand, in
November 2020. Due to COVID-19 pandemic the conference was held
virtually. The 187 full papers presented were carefully reviewed
and selected from 618 submissions. The papers address the emerging
topics of theoretical research, empirical studies, and applications
of neural information processing techniques across different
domains. The third volume, LNCS 12534, is organized in topical
sections on biomedical information; neural data analysis; neural
network models; recommender systems; time series analysis.
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Neural Information Processing - 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23-27, 2020, Proceedings, Part I (Paperback, 1st ed. 2020)
Hai-Qin Yang, Kitsuchart Pasupa, Andrew Chi-Sing Leung, James T. Kwok, Jonathan H. Chan, …
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R3,129
Discovery Miles 31 290
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Ships in 10 - 15 working days
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The three-volume set of LNCS 12532, 12533, and 12534 constitutes
the proceedings of the 27th International Conference on Neural
Information Processing, ICONIP 2020, held in Bangkok, Thailand, in
November 2020. Due to COVID-19 pandemic the conference was held
virtually.The 187 full papers presented were carefully reviewed and
selected from 618 submissions. The papers address the emerging
topics of theoretical research, empirical studies, and applications
of neural information processing techniques across different
domains. The first volume, LNCS 12532, is organized in topical
sections on human-computer interaction; image processing and
computer vision; natural language processing.
Regularization is a dominant theme in machine learning and
statistics due to its prominent ability in providing an intuitive
and principled tool for learning from high-dimensional data. As
large-scale learning applications become popular, developing
efficient algorithms and parsimonious models become promising and
necessary for these applications. Aiming at solving large-scale
learning problems, this book tackles the key research problems
ranging from feature selection to learning with mixed unlabeled
data and learning data similarity representation. More
specifically, we focus on the problems in three areas: online
learning, semi-supervised learning, and multiple kernel learning.
The proposed models can be applied in various applications,
including marketing analysis, bioinformatics, pattern recognition,
etc.
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