Fundamentals
Contributor(s)
Morik, Katharina (editor)
Marwedel, Peter (editor)
Language
EnglishAbstract
Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters.
Keywords
Resource-Constrained Data Analysis; Resource-Aware Machine Learning; Embedded Systems and Machine Learning; Big Data and Machine Learning; Artificial Intelligence; Highly Distributed Data; ML on Small devices; Data mining for Ubiquitous System Software Cyber-physical systems Machine learning in high-energy physics Machine learning for knowledge discoveryDOI
10.1515/9783110785944ISBN
9783110785944, 9783110785937, 9783110786125, 9783110785944Publisher
De GruyterPublisher website
https://www.degruyter.com/Publication date and place
Berlin/Boston, 2022Imprint
De GruyterSeries
De Gruyter STEM, Volume 1Classification
Chemistry
Algorithms and data structures
Databases
Computer networking and communications
Artificial intelligence