Название: Machine Learning under Resource Constraints, Volume 1: FundamentalsАвтор: Katharina Morik, Peter Marwedel
Издательство: De Gruyter
Год: 2023
Страниц: 506
Язык: английский
Формат: pdf (true), epub
Размер: 45.7 MB
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.
Автор: Марина Дяченко, Сергей Дяченко
Название: Age of Information: Foundations and Applications
Название: Distributed Optimization in Networked Systems: Algorithms and Applications
Автор: Григорий Володин
Название: Systems Engineering Competency Assessment Guide
