Distributed Machine Learning and Computing: Theory Applications: 2

This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. It is suitable for students and researchers interested in conducting research in multidisciplinary areas that rely on distributed machine learning and computing techniques. This book focuses on a wide range of distributed machine learning and computing algorithms and their applications in healthcare and engineering systems. The contributors explore how these techniques can be applied to different real-world problems. It is suitable for students and researchers interested in conducting research in multidisciplinary areas that rely on distributed machine learning and computing techniques. Specifies the value of efficient theoretical methods in dealing with large-scale decision-making problems; Provides an investigation of distributed machine learning and optimization algorithms for large-scale networks; Includes basics and mathematical foundations needed to analyze and address the interdependent complex networks.