Go back

Machine Learning And Knowledge Discovery In Databases European Conference ECML PKDD 2019 W Rzburg Germany September 20 2019 Proceedings Part 1 LNAI 11906(1st Edition)

Authors:

Ulf Brefeld ,Elisa Fromont ,Andreas Hotho ,Arno Knobbe ,Marloes Maathuis ,Celine Robardet

Free machine learning and knowledge discovery in databases european conference ecml pkdd 2019 w rzburg germany
9 ratings
Cover Type:Hardcover
Condition:Used

In Stock

Include with your book

Free shipping: April 06, 2024
Access to 3 Million+ solutions Free
Ask 10 Questions from expert 200,000+ Expert answers
7 days-trial

Total Price:

$0

List Price: $8.45 Savings: $8.45(100%)

Book details

ISBN: 3030461491, 978-3030461492

Book publisher: Springer

Get your hands on the best-selling book Machine Learning And Knowledge Discovery In Databases European Conference ECML PKDD 2019 W Rzburg Germany September 20 2019 Proceedings Part 1 LNAI 11906 1st Edition for free. Feed your curiosity and let your imagination soar with the best stories coming out to you without hefty price tags. Browse SolutionInn to discover a treasure trove of fiction and non-fiction books where every page leads the reader to an undiscovered world. Start your literary adventure right away and also enjoy free shipping of these complimentary books to your door.

Machine Learning And Knowledge Discovery In Databases European Conference ECML PKDD 2019 W Rzburg Germany September 20 2019 Proceedings Part 1 LNAI 11906 1st Edition Summary: The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019.The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows:Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization.Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing.Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track.Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.