Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning Under Resource Constraints - Applications

Machine Learning Under Resource Constraints - Applications

Morik, Katharina
Rahnenführer, Jörg
Wietfeld, Christian

Paperback

Series: de Gruyter Stem

Technology & EngineeringGeneral SciencePhysics

ISBN10: 3110785978
ISBN13: 9783110785975
Publisher: de Gruyter
Published: Dec 31 2022
Pages: 478
Weight: 1.67
Height: 0.97 Width: 6.69 Depth: 9.61
Language: English

Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering.

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