Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Machine Learning and Knowledge Discovery in Databases by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319712499
Publisher: Springer International Publishing Publication: December 29, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319712499
Publisher: Springer International Publishing
Publication: December 29, 2017
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Thermal Plasma Processing of Ilmenite by
Cover of the book Bioengineering by
Cover of the book Activating the Tools of Social Media for Innovative Collaboration in the Enterprise by
Cover of the book Additive Manufacturing of Metals by
Cover of the book The Maritime Turn in EU Foreign and Security Policies by
Cover of the book Advanced Data Mining and Applications by
Cover of the book Hole Conductor Free Perovskite-based Solar Cells by
Cover of the book Recent Advances in Systems Safety and Security by
Cover of the book Evaluating e-Participation by
Cover of the book Multicriteria Analysis in Finance by
Cover of the book Writing Case Reports by
Cover of the book Racialization, Racism, and Anti-Racism in the Nordic Countries by
Cover of the book Well-Being in Contemporary Society by
Cover of the book Design, User Experience, and Usability: Users and Interactions by
Cover of the book Nanostructured Materials for Energy Related Applications by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy