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Katharina Morik Machine Learning under Resource Constraints - Discov (Paperback)
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eBay item number:335266521617
Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- Book Title
- Machine Learning under Resource Constraints - Discovery in Physic
- Publication Name
- Machine Learning under Resource Constraints-Discovery in Physics
- Title
- Machine Learning under Resource Constraints - Discovery in Physic
- Contributor
- Wolfgang Rhode (Edited by)
- Format
- Trade Paperback
- ISBN-10
- 3110785951
- EAN
- 9783110785951
- ISBN
- 9783110785951
- Publisher
- DE Gruyter Gmbh, Walter
- Genre
- Computing & Internet
- Release Date
- 31/12/2022
- Release Year
- 2022
- Language
- English
- Country/Region of Manufacture
- DE
- Item Height
- 240mm
- Item Length
- 9.4 in
- Item Weight
- 21.8 Oz
- Series
- De Gruyter Stem Ser.
- Subject Area
- Computers, Science
- Subject
- Programming / Algorithms, Data Processing, Databases / Data Mining, Chemistry / General, Information Technology
- Publication Year
- 2022
- Type
- Textbook
- Item Width
- 6.7 in
- Number of Pages
- 363 Pages
About this product
Product Information
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 2 covers machine learning for knowledge discovery in particle and astroparticle physics. Their instruments, e.g., particle detectors or telescopes, gather petabytes of data. Here, machine learning is necessary not only to process the vast amounts of data and to detect the relevant examples efficiently, but also as part of the knowledge discovery process itself. The physical knowledge is encoded in simulations that are used to train the machine learning models. At the same time, the interpretation of the learned models serves to expand the physical knowledge. This results in a cycle of theory enhancement supported by machine learning.
Product Identifiers
Publisher
DE Gruyter Gmbh, Walter
ISBN-10
3110785951
ISBN-13
9783110785951
eBay Product ID (ePID)
6058384416
Product Key Features
Publication Name
Machine Learning under Resource Constraints-Discovery in Physics
Format
Trade Paperback
Language
English
Subject
Programming / Algorithms, Data Processing, Databases / Data Mining, Chemistry / General, Information Technology
Series
De Gruyter Stem Ser.
Publication Year
2022
Type
Textbook
Subject Area
Computers, Science
Number of Pages
363 Pages
Dimensions
Item Length
9.4 in
Item Width
6.7 in
Item Weight
21.8 Oz
Additional Product Features
LCCN
2022-949268
Lc Classification Number
Q325.5.M32138 2023
Grade from
College Graduate Student
Grade to
College Graduate Student
Copyright Date
2023
Target Audience
Scholarly & Professional
Dewey Decimal
006.31
Dewey Edition
23
Illustrated
Yes
Item description from the seller
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eBay item number:335266521617
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60502, United States
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