Optimization Learning Algorithms And Applications
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Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2024-12-25
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-25 with Computers categories.
This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections:- Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2025-09-30
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.
The two-volume set CCIS 2617 and 2618 constitutes the refereed post-conference proceedings of the 5th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2025, held in Sesti Levante, Italy, during April 28–30, 2025. The 38 revised full papers presented in these proceedings were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Part I: Optimization; Optimization in Control Systems Design; Artificial Intelligence in Healthcare and Medicine; and Deep Learning. Part II: Optimization in the SDG context; Machine Learning; and Machine Learning and Artificial Intelligence in Robotics.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2025-09-30
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-30 with Computers categories.
The two-volume set CCIS 2617 and 2618 constitutes the refereed post-conference proceedings of the 5th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2025, held in Sesti Levante, Italy, during April 28–30, 2025. The 38 revised full papers presented in these proceedings were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Part I: Optimization; Optimization in Control Systems Design; Artificial Intelligence in Healthcare and Medicine; and Deep Learning. Part II: Optimization in the SDG context; Machine Learning; and Machine Learning and Artificial Intelligence in Robotics.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2021-12-02
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-02 with Computers categories.
This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from 134 submissions. They are organized in the topical sections on optimization theory; robotics; measurements with the internet of things; optimization in control systems design; deep learning; data visualization and virtual reality; health informatics; data analysis; trends in engineering education.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2024-12-25
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-25 with Computers categories.
This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections:- Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This book constitutes the proceedings of the Second International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022, held in Bragança, Portugal, in October 2022. The 53 full papers and 3 short papers were thoroughly reviewed and selected from 145 submissions. They are organized in the topical sections on Machine and Deep Learning; Optimization; Artificial Intelligence; Optimization in Control Systems Design; Measurements with the Internet of Things; Trends in Engineering Education; Advances and Optimization in Cyber-Physical Systems; and Computer vision based on learning algorithms.
Optimization In Machine Learning And Applications
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Author : Anand J. Kulkarni
language : en
Publisher: Springer Nature
Release Date : 2019-11-29
Optimization In Machine Learning And Applications written by Anand J. Kulkarni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Technology & Engineering categories.
This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher: Springer
Release Date : 2025-01-29
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-29 with Computers categories.
This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in July 2024. The 41 papers presented here were carefully reviewed and selected from 105 submissions. They have been organized in the two volumes under the following topical sections: - Part I: Learning Algorithms in Engineering Education; Machine Learning; Deep Learning; Optimization in the SDG context. Part II: Optimization in Control Systems Design; Optimization.
Optimization Learning Algorithms And Applications
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Author : Ana I. Pereira
language : en
Publisher:
Release Date : 2021
Optimization Learning Algorithms And Applications written by Ana I. Pereira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.
This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from 134 submissions. They are organized in the topical sections on optimization theory; robotics; measurements with the internet of things; optimization in control systems design; deep learning; data visualization and virtual reality; health informatics; data analysis; trends in engineering education.
Metaheuristics For Machine Learning
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Author : Kanak Kalita
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-30
Metaheuristics For Machine Learning written by Kanak Kalita and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-30 with Computers categories.
METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristic optimization algorithms is experiencing rapid growth, both in academic research and industrial applications. These nature-inspired algorithms, which draw on phenomena like evolution, swarm behavior, and neural systems, have shown remarkable efficiency in solving complex optimization problems. With advancements in machine learning and artificial intelligence, the application of metaheuristic optimization techniques has expanded, demonstrating significant potential in optimizing machine learning models, hyperparameter tuning, and feature selection, among other use-cases. In the industrial landscape, these techniques are becoming indispensable for solving real-world problems in sectors ranging from healthcare to cybersecurity and sustainability. Businesses are incorporating metaheuristic optimization into machine learning workflows to improve decision-making, automate processes, and enhance system performance. As the boundaries of what is computationally possible continue to expand, the integration of metaheuristic optimization and machine learning represents a pioneering frontier in computational intelligence, making this book a timely resource for anyone involved in this interdisciplinary field. Metaheuristics for Machine Learning: Algorithms and Applications serves as a comprehensive guide to the intersection of nature-inspired optimization and machine learning. Authored by leading experts, this book seamlessly integrates insights from computer science, biology, and mathematics to offer a panoramic view of the latest advancements in metaheuristic algorithms. You’ll find detailed yet accessible discussions of algorithmic theory alongside real-world case studies that demonstrate their practical applications in machine learning optimization. Perfect for researchers, practitioners, and students, this book provides cutting-edge content with a focus on applicability and interdisciplinary knowledge. Whether you aim to optimize complex systems, delve into neural networks, or enhance predictive modeling, this book arms you with the tools and understanding you need to tackle challenges efficiently. Equip yourself with this essential resource and navigate the ever-evolving landscape of machine learning and optimization with confidence. Audience The book is aimed at a broad audience encompassing researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics. The detailed but accessible content makes it a must-have for both academia and industry professionals interested in the optimization aspects of machine learning algorithms.