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Machine Learning and Knowledge Discovery in Databases
13 Angebote vergleichen
Bester Preis: € 47,72 (vom 01.12.2017)Machine Learning and Knowledge Discovery in Databases (2017)
ISBN: 9783319712451 bzw. 3319712454, in Deutsch, Springer Shop, Taschenbuch, neu.
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track. Soft cover.
Machine Learning and Knowledge Discovery in Databases (2017)
ISBN: 9783319712499 bzw. 3319712497, vermutlich in Englisch, Springer Shop, neu, E-Book, elektronischer Download.
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning. Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning. Part III: applied data science track; nectar track; and demo track. eBook.
Machine Learning and Knowledge Discovery in Databases (2017)
ISBN: 3319712454 bzw. 9783319712451, in Deutsch, neu.
Machine Learning and Knowledge Discovery in Databases (2017)
ISBN: 9783319712499 bzw. 3319712497, in Englisch, Springer, Springer, Springer, neu, E-Book, elektronischer Download.
The three volume proceedings LNAI 10534 - 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The tot.
Machine Learning and Knowledge Discovery in Databases (2017)
ISBN: 9783319712451 bzw. 3319712454, in Deutsch, neu.
The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions, there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection, computer vision, ensembles and meta learning, feature selection and extraction, kernel methods, learning and optimization, matrix and tensor factorization, networks and graphs, neural networks and deep learning. Part II: pattern and sequence mining, privacy and security, probabilistic models and methods, recommendation, regression, reinforcement learning, subgroup discovery, time series and streams, transfer and multi-task learning, unsupervised and semisupervised learning. Part III: applied data science track, nectar track, and demo track.
/ Hollmén / Todorovski / Vens / Džeroski | Machine Learning and Knowledge Discovery in Databases | Springer | 1st ed. 2017 | 2018
ISBN: 9783319712451 bzw. 3319712454, in Deutsch, Springer, neu.
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, . Notes in Computer Science, Band 10535) (2017)
ISBN: 9783319712451 bzw. 3319712454, in Englisch, Springer, Taschenbuch, neu, Erstausgabe.
Von Händler/Antiquariat, Amazon.de.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Machine Learning and Knowledge Discovery in Databases
ISBN: 9783319712468 bzw. 3319712462, in Deutsch, Springer Nature, neu, E-Book.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Machine Learning and Knowledge Discovery in Databases
ISBN: 9783319712734 bzw. 331971273X, in Deutsch, Springer Nature, neu, E-Book.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen