Fundamentals

• Other Authors: Morik, Katharina (Editor), Marwedel, Peter (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Berlin/Boston De Gruyter 2022
• Series: De Gruyter STEM Volume 1
• Subjects: Chemistry; Algorithms & data structures; Databases; Computer networking & communications; Artificial intelligence; 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 discovery
• Online Access: OAPEN Library: download the publication; OAPEN Library: description of the publication

Summary

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.

Physical Description

1 electronic resource (491 p.)

ISBN

9783110785944
9783110785937
9783110786125

Access

Open Access