Machine Learning Under Resource Constraints - Fundamentals
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 a...
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| Formato: | Libro |
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De Gruyter
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=3501567&site=ehost-live header: @attributes: shortDbName: nlebk uiTerm: 3501567 longDbName: eBook Collection (EBSCOhost) uiTag: AN controlInfo: bkinfo: btl: Machine Learning Under Resource Constraints - Fundamentals aug: au: Katharina Morik Peter Marwedel sertl: Machine Learning Under Resource Constraints isbn: 9783110785937 9783110785944 9783110786125 imageinfo: pubinfo: dt: @attributes: year: 2023 month: 01 day: 01 dtAvail: @attributes: year: 2023 month: 02 day: 10 vid: 00001 pub: De Gruyter pubContract: De Gruyter place: Berlin price: 0.01 limitsGroup: maxCheckoutDays: 1500 pda: N printPagesOffline: 100 printPagesOnline: 100 previewPages: 10000 prePubGroup: dewey: @attributes: class: 006.31 item: 006 .31 lc: @attributes: class: Q325.5 item: Q 325 .5 artinfo: ui: 3501567 1356977369 formats: fmt: – @attributes: type: EB doid: NL$3501567$PDF caption: PDF download: Y – @attributes: type: EK doid: NL$3501567$EPUB caption: EPUB download: Y tig: atl: Machine Learning Under Resource Constraints - Fundamentals ptl: Machine Learning Under Resource Constraints - Fundamentals aug: au: Katharina Morik Peter Marwedel su: Machine learning sug: subj: COMPUTERS / Information Technology COMPUTERS / Data Science / General COMPUTERS / Data Science / Data Analytics COMPUTERS / Programming / Algorithms Machine learning ab: 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. Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to the different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Several machine learning methods are inspected with respect to their resource requirements and how to enhance their scalability on diverse computing architectures ranging from embedded systems to large computing clusters. pubtype: eBook doctype: Book ougenre: Book language: English copyright: @attributes: flag: N copyrightText: holdings: @attributes: islocal: N |
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