IoT streams for data-driven predictive maintenance and IoT, edge, and mobile for embedded machine learning: Second International Workshop, IoT Streams 2020 and First International Workshop, ITEM 2020, co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020 : revised selected papers

Show other versions (1)

Stream Learning -- Feature Learning -- Unsupervised Machine Learning -- Hardware -- Methods -- Quantization.

Saved in:

Bibliographic Details
Corporate Authors:	IoT Streams, Online (Author) , ITEM (Author)
Other Authors:	Gama, João (Editor) , Pashami, Sepideh (Editor) , Bifet, Albert (Editor) , Sayed-Mouchaweh, Moamar (Editor) , Fröning, Holger (Editor) , Pernkopf, Franz (Editor) , Schiele, Gregor (Editor) , Blott, Michaela (Editor)
Format:	Conference Paper
Language:	English
Published:	Cham Springer International Publishing 2020. Cham Imprint: Springer 2020.
Edition:	1st ed. 2020.
Series:	Communications in Computer and Information Science 1325 Springer eBook Collection
DOI:	10.1007/978-3-030-66770-2
Subjects:	Konferenzschrift Maschinelles Lernen Internet der Dinge
Online Access:	Resolving-System, lizenzpflichtig: https://doi.org/10.1007/978-3-030-66770-2
Author Notes:	Joao Gama, Sepideh Pashami, Albert Bifet, Moamar Sayed-Mouchawe, Holger Fröning, Franz Pernkopf, Gregor Schiele, Michaela Blott (eds.)

Description
Summary:	Stream Learning -- Feature Learning -- Unsupervised Machine Learning -- Hardware -- Methods -- Quantization. This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.
Physical Description:	Online Resource
ISBN:	9783030667702
DOI:	10.1007/978-3-030-66770-2