Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 Proceedings: 11052 - Brossura

Brossura

ISBN 10: 3030109275 ISBN 13: 9783030109271

Casa editrice: Springer-Nature New York Inc, 2019

Riassunto

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 learningensemble 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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Dalla quarta di copertina

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 learningensemble 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.

Dettagli dell'edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2019
• Lingua: Inglese
• ISBN 10: 3030109275
• ISBN 13: 9783030109271
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 866
• Redattore: Berlingerio Michele, Bonchi Francesco, Gärtner Thomas, Hurley Neil, Ifrim Georgiana
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania