ECML PKDD 2018 Workshops
DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers
Published on 8. March 2019
Book
Paperback/Softback
IX, 127 pages
978-3-030-14879-9 (ISBN)
Description
This book constitutes revised selected papers from the workshops DMLE and IoTStream, held at the 18
th
European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, in Dublin, Ireland, in September 2018.
The 8 full papers presented in this volume were carefully reviewed and selected from a total of 12 submissions.
The 8 full papers presented in this volume were carefully reviewed and selected from a total of 12 submissions.
The workshops included are:
DMLE 2018: First Workshop on Decentralized Machine Learning at the EdgeIoTStream 2018: 3rd Workshop on IoT Large Scale Machine Learning from Data Streams
More details
Series
Edition
2019 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
27 farbige Abbildungen, 16 s/w Abbildungen
IX, 127 p. 43 illus., 27 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 8 mm
Weight
224 gr
ISBN-13
978-3-030-14879-9 (9783030148799)
DOI
10.1007/978-3-030-14880-5
Schweitzer Classification
Other editions
Additional editions
Anna Monreale | Carlos Alzate | Michael Kamp
ECML PKDD 2018 Workshops
DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers
E-Book
03/2019
Springer
€53.49
Available for download
Content
Decentralized Machine Learning on the Edge. - Sparsity in Deep Neural Networks---An Empirical Investigation with TensorQuant. - Asynchronous Federated Learning for Geospatial Applications. - Generalizing Knowledge in Decentralized Rule-based Models. - Introducing Noise in Decentralized Training of Neural Networks. - Query Log Analysis: Detecting Anomalies in DNS Traffic at a TLD Resolver. - Multimodal Tweet Sentiment Classification Algorithm Based on Attention Mechanism. - Active Learning by Clustering for Drifted Data Stream Classification. - Self Hyper-Parameter Tuning for Stream Recommendation Algorithms. - Deep Online Storage-Free Learning on Unordered Image Streams. - Fault Prognostics for the Predictive Maintenance of Wind Turbines: State of the Art.