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...
Uložené v:
| Hlavný autor: | |
|---|---|
| Médium: | E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Berlin/Boston
De Gruyter
2022
Walter de Gruyter GmbH |
| Vydanie: | 1 |
| Predmet: | |
| ISBN: | 9783110786125, 3110786125 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | 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. |
|---|---|
| AbstractList | 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. |
| Author | Katharina Morik, Peter Marwedel, Katharina Morik, Peter Marwedel, Jens Buß, Andreas Becker |
| Author_xml | – sequence: 1 fullname: Katharina Morik, Peter Marwedel, Katharina Morik, Peter Marwedel, Jens Buß, Andreas Becker |
| BookMark | eNotj01LxDAYhCN-oF37Dzzk5qmQ9E2axpuWXRUqgojXkqZv12pNNGn_vy27p2GYh2EmIWfOOzwhCXDOVCm1gFOSalUefMFzeUESDlIxLnkpLkka4xdjDHIQDOQVuXsx9nNwSGs0wQ1uT2fXYaBvGP0cLNLKuzgFM7gp0ozultT8oJvMGK_Jeb8IpkfdkI_d9r16yurXx-fqvs4MByWKTOvSytzkvUGFBRRti1LkrMyh7zhrlW3Fut0WWFhjmcaOWyV7pjoueGsBNuT2UPwb_N-McWqw9f7bLjOCGZvtQ6W4XL8u5M2RxDDi3jcrFxtQWgul4B9rAFSN |
| ContentType | eBook |
| DBID | YSPEL |
| DEWEY | 006.31 |
| DatabaseName | Perlego |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISBN | 3110785943 9783110785944 |
| Edition | 1 |
| ExternalDocumentID | EBC7156125 3799477 |
| Genre | Electronic books |
| GroupedDBID | A7I ALMA_UNASSIGNED_HOLDINGS I4C V1H YSPEL |
| ID | FETCH-LOGICAL-a13746-998c52a2fae7e636bbe5420823fd10b7cb40785c6e6cac09ed1c75f07d141bc33 |
| ISBN | 9783110786125 3110786125 |
| IngestDate | Wed Apr 23 01:02:02 EDT 2025 Tue Dec 02 16:48:41 EST 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-a13746-998c52a2fae7e636bbe5420823fd10b7cb40785c6e6cac09ed1c75f07d141bc33 |
| OCLC | 1357015184 |
| PQID | EBC7156125 |
| PageCount | 505 pages |
| ParticipantIDs | proquest_ebookcentral_EBC7156125 perlego_books_3799477 |
| PublicationCentury | 2000 |
| PublicationDate | 2022 |
| PublicationDateYYYYMMDD | 2022-01-01 |
| PublicationDate_xml | – year: 2022 text: 2022 |
| PublicationDecade | 2020 |
| PublicationPlace | Berlin/Boston |
| PublicationPlace_xml | – name: Berlin/Boston |
| PublicationYear | 2022 |
| Publisher | De Gruyter Walter de Gruyter GmbH |
| Publisher_xml | – name: De Gruyter – name: Walter de Gruyter GmbH |
| SSID | ssj0003234035 |
| Score | 2.3355799 |
| Snippet | Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by... |
| SourceID | proquest perlego |
| SourceType | Publisher |
| SubjectTerms | COMPUTERS |
| TableOfContents | Intro -- Contents -- Preface -- 1 Introduction -- Data Gathering and Resource Measuring -- 3 Streaming Data, Small Devices -- 4 Structured Data -- 5 Cluster Analysis -- 6 Hardware-Aware Execution -- 7 Memory Awareness -- 8 Communication Awareness -- 9 Energy Awareness -- Bibliography -- Index -- List of Contributors |
| Title | Machine Learning under Resource Constraints - Fundamentals |
| URI | https://www.perlego.com/book/3799477/machine-learning-under-resource-constraints-fundamentals-pdf https://ebookcentral.proquest.com/lib/[SITE_ID]/detail.action?docID=7156125 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1JS8QwFA6u4Mkdx40cxMsQaJO2ab2puIGKB1FvQ5q-iqidsZ1x-fe-ZNKOjgfx4CWkoeTwvUeSt36E7MRxlKucA0MDKGWoIcDSXANTQnsaDY5M2zrum3N5eRnf3SVXjr21snQCsiji9_ek96-ixjUUtimd_YO4m01xAecodBxR7DiOvYibT0fIZPMioW6Zem8pbsvGQW-5OS0jRL9qs_axKQEZdvZvntUX3fLhsc6xQCO6aM7sC1W-QTaM6I9Sep23gPMxb8GtjcG3M9TAcvBhpifP6ek3m1IYizAOk2FbxrFm1EcHh9I3hJrhbu-FGe4uE-N2RCaTZNrEcY0JvC_PGk-X4CLwDJ3ebA_KJ7jv_rj27F1-vUCmwRR4LJIJKJbIfE1rQd0pt0z2HJC0BpJaIGkNJP0CJGX0K5Ar5Ob46PrwlDmKCaZ8IYOIobWpQ654rkBCJKI0hdBkHHCRZ76XSp2aQGeoI4i00l4Cma9lmHsy8wM_1UKskqmiW8AaoVolQiVS4xNcB4HQSkEWBLgxxzNOcL9FVhwAHaMfVUfIJAmkbBFaw9GxEXKXltsZgb3--y8bZG4k700y1S8HsEVm9Gv_oSq3rUQ-Ae9GH_c |
| linkProvider | Open Access Publishing in European Networks |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.title=Machine+Learning+under+Resource+Constraints+-+Fundamentals&rft.au=Morik%2C+Katharina&rft.au=Marwedel%2C+Peter&rft.date=2022-01-01&rft.pub=Walter+de+Gruyter+GmbH&rft.isbn=9783110785944&rft.externalDocID=EBC7156125 |
| thumbnail_l | http://cvtisr.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fwww.perlego.com%2Fbooks%2FRM_Books%2Fde_gruyter_frmluoo%2F9783110786125.jpg |