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Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III (Lecture Notes in Computer Science)

By: Alice Marascu (Edited by) , Brian MacNamee (Edited by) , Edward Curry (Edited by) , Elizabeth Daly (Edited by) , Fabio Pinelli (Edited by) , Michele Berlingerio (Edited by) , Neil Hurley (Edited by) , Ulf Brefeld (Edited by)

Extended Catalogue

Ksh 10,250.00

Format: Paperback or Softback

ISBN-10: 3030109968

ISBN-13: 9783030109967

Collection / Series: Lecture Notes in Computer Science

Collection Type: Publisher collection

Edition statement: 2019 ed.

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jan 18th, 2019

Publication Status: Active

Product extent: 706 Pages

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The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The contributions were organized in topical sections named as follows: Part I: adversarial learning;

The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. 

The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. 

The contributions were organized in topical sections named as follows:
Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learning; ensemble methods; and evaluation.
Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning.
Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.


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