Order Analysis Deep Learning And Connections To Optimization
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Order Analysis, Deep Learning, and Connections to Optimization
This book introduces readers to order analysis and various aspects of deep learning, and describes important connections to optimization, such as nonlinear optimization as well as vector and set optimization. Besides a review of the essentials, this book consists of two main parts. The first main part focuses on the introduction of order analysis as an application-driven theory, which allows to treat order structures with an analytical approach. Applications of order analysis to nonlinear optimization, as well as vector and set optimization with fixed and variable order structures, are discussed in detail. This means there are close ties to finance, operations research, and multicriteria decision making. Deep learning is the subject of the second main part of this book. In addition to the usual basics, the focus is on gradient methods, which are investigated in the context of complex models with a large number of parameters. And a new fast variant of a gradient method is presented in this part. Finally, the deep learning approach is extended to data sets given by set-valued data. Although this set-valued approach is more computationally intensive, it has the advantage of producing more robust predictions. This book is primarily intended for researchers in the fields of optimization, order theory, or artificial intelligence (AI), but it will also benefit graduate students with a general interest in these fields. The book assumes that readers have a basic understanding of functional analysis or at least basic analysis. By unifying and streamlining existing approaches, this work will also appeal to professionals seeking a comprehensive and straightforward perspective on AI or order theory approaches.
Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
Author: Essam Halim Houssein
language: en
Publisher: Springer Nature
Release Date: 2022-06-04
This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.
Proceeding of the International Conference on Connected Objects and Artificial Intelligence (COCIA2024)
’This book presents recent advances on Connected Objects, Systems, Telecommunications, Artificial Intelligence, and Electronic Engineering. On the connected objects side, the proceedings covered advancements in areas like sensor miniaturization, and networking to enable ever-more ubiquitous and autonomous IoT deployments. The AI-focused contributions explored novel machine learning architectures and training techniques tailored for resource-constrained edge devices. Key breakthroughs included federated learning models. In the telecommunications realm, the proceedings examined the critical role of 5G, 6G, and satellite communications in providing the high-bandwidth, low-latency connectivity required to unlock the full potential of AI-powered connected systems. This book is a collection of high-quality research papers presented at the 2nd International Conference on Connected Objects and Artificial Intelligence (COCIA'2024), held at High School of Technology, Hassan II University, Casablanca, Morocco, during 08–10 May 2024. This book features cutting-edge research and insights at the intersection of the important technology domains, Connected Objects, Systems, Telecommunications, Artificial Intelligence, and Electronic Engineering. It is designed for researchers, academicians, professionals, and graduates seeking to deepen their understanding and expertise at the intersection of IoT, AI, Telecommunications, and Electronic Engineering. This book includes: In-depth exploration of the latest advancements in connected objects and systems to enable autonomous IoT deployments. Detailed examinations of cutting-edge AI techniques optimized for edge computing environments, including federated learning and IA model compression. Insights into the critical role of 5G, 6G, and satellite communications in providing the high-performance connectivity required to unlock the full potential of intelligent, AI-powered IoT applications. With contributions from leading experts across academia and industry, this book equips readers with the knowledge and tools to drive innovation at the forefront of the connected intelligence revolution. It is an essential resource for anyone seeking to advance the state of the art in this rapidly evolving field.