Computational Intelligence for High-dimensional Machine Learning A Feature Selection perspective and its real-world applications

Zhou Yu Zhang, Xiao Kwong, Sam
Heftet / 2025 / Engelsk

Produktdetaljer

ISBN
9789819626861
Publisert
2025-04-11
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter
Zhou Yu
Zhang, Xiao
Kwong, Sam

Biographical note

Prof. Yu Zhou received Ph.D. degree in computer science from the City University of Hong Kong, Hong Kong, in 2017. From 2016 to 2017, he was a research associate, postdoctoral research fellow and visiting scholar in City University of Hong Kong. In 2017, he joined College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China, as an assistant professor. He is currently a tenured associate professor. His current research interests include computational intelligence, machine learning and intelligent information processing. He has co-authored over 50 international journal and conference papers, including IEEE TEVC, IEEE TCYB, IEEE TIM, IEEE TETCI, IEEE IOTJ, etc. He was the recipient of outstanding paper award from Computer Academy of Guangdong and the outstanding reviewer award of EJOR.

Prof. Xiao Zhang received the B.Eng. and M.Eng. degrees from South-Central Minzu University, Wuhan, China, in 2009 and 2011, respectively. In 2015, he was a visiting scholar with the Utah State University, Utah, USA. He received his Ph.D. degree from Department of Computer Science in City University of Hong Kong, Hong Kong, 2016. During 2016–2019, he was a postdoc research fellow at Singapore University of Technology and Design. Currently, he is an associate professor with College of Computer Science, South-Central Minzu University, China. His research interests include algorithms design and analysis, combinatorial optimization, wireless and UAV networking.

Prof. Sam Kwong is the chair professor of Computational Intelligence and concurrently as associate vice-president (Strategic Research) of Lingnan University. Professor Kwong is a distinguished scholar in evolutionary computation, artificial intelligence (AI) solutions and image/video processing, with a strong record of scientific innovations and real-world impacts. Professor Kwong was listed as one of the top 2% of the world’s most cited scientists, according to the Stanford University report. He was listed as one of the top 1% of the world’s most cited scientists by Clarivate in 2022. He has also been actively engaged in knowledge transfer  between academia and industry. He was elevated to IEEE Fellow in 2014 for his contributions to optimization techniques in cybernetics and video coding.

Computational Intelligence for High-dimensional Machine Learning A Feature Selection perspective and its real-world applications

Zhou Yu Zhang, Xiao Kwong, Sam
Heftet / 2025 / Engelsk
Zhou Yu Zhang, Xiao Kwong, Sam
Heftet / 2025 / Engelsk
Nettpris:
801,-
Laveste pris siste 30 dager: 801,-
Kommer i salg {date}
Klikk og hent
This book focuses on the modelling and optimization aspects of the feature selection problem through computational intelligence methods in complex, high-dimensional supervised machine learning. To aid readers in conducting research in this field, it covers fundamental concepts and state-of-the-art algorithms. This book also provides a detailed insight into applying these algorithms into real-world applications. The authors begin by introducing the definition high-dimensional machine learning (ML) problems and the challenges they pose. Subsequently, they delve into dimension reduction methods for high-dimensional ML, including global and local feature selection (FS) techniques. This book also comprehensively presents computational intelligence methods such as evolutionary computation and deep neural networks for FS, supported by both theoretical and empirical evidence. Furthermore, this book explores real-world scenario applications involving high-dimensional ML, particularly in the context of smart cities, bioinformatics and industrial informatics.  This book is a suitable read for postgraduates and researchers who are interested in the research areas of computational intelligence, soft computing, machine learning and deep learning. Professionals and practitioners within these related fields will also benefit from this book.
Les mer
This book focuses on the modelling and optimization aspects of the feature selection problem through computational intelligence methods in complex, high-dimensional supervised machine learning.
Introduction of High Dimensional Machine Learning.- Feature selection and computational Intelligence Methods.- Evolutionary algorithm based global feature selection.- Evolutionary algorithm based local feature selection.- Deep neural network based hybrid feature selection.- Real-world case study.- Conclusions.
Les mer
Is the first trial to combine computational intelligence and feature selection for high-dimensional machine learning Presents state-of-the-art computational intelligence methods and algorithms Provides real-world applications and case studies
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Relaterte produkter

This book focuses on the modelling and optimization aspects of the feature selection problem through computational intelligence methods in complex, high-dimensional supervised machine learning. To aid readers in conducting research in this field, it covers fundamental concepts and state-of-the-art algorithms. This book also provides a detailed insight into applying these algorithms into real-world applications. The authors begin by introducing the definition high-dimensional machine learning (ML) problems and the challenges they pose. Subsequently, they delve into dimension reduction methods for high-dimensional ML, including global and local feature selection (FS) techniques. This book also comprehensively presents computational intelligence methods such as evolutionary computation and deep neural networks for FS, supported by both theoretical and empirical evidence. Furthermore, this book explores real-world scenario applications involving high-dimensional ML, particularly in the context of smart cities, bioinformatics and industrial informatics.  This book is a suitable read for postgraduates and researchers who are interested in the research areas of computational intelligence, soft computing, machine learning and deep learning. Professionals and practitioners within these related fields will also benefit from this book.
Les mer
This book focuses on the modelling and optimization aspects of the feature selection problem through computational intelligence methods in complex, high-dimensional supervised machine learning.
Introduction of High Dimensional Machine Learning.- Feature selection and computational Intelligence Methods.- Evolutionary algorithm based global feature selection.- Evolutionary algorithm based local feature selection.- Deep neural network based hybrid feature selection.- Real-world case study.- Conclusions.
Les mer
Is the first trial to combine computational intelligence and feature selection for high-dimensional machine learning Presents state-of-the-art computational intelligence methods and algorithms Provides real-world applications and case studies
Les mer
GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
Les mer

Produktdetaljer

ISBN
9789819626861
Publisert
2025-04-11
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Forfatter
Zhou Yu
Zhang, Xiao
Kwong, Sam

Biographical note

Prof. Yu Zhou received Ph.D. degree in computer science from the City University of Hong Kong, Hong Kong, in 2017. From 2016 to 2017, he was a research associate, postdoctoral research fellow and visiting scholar in City University of Hong Kong. In 2017, he joined College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China, as an assistant professor. He is currently a tenured associate professor. His current research interests include computational intelligence, machine learning and intelligent information processing. He has co-authored over 50 international journal and conference papers, including IEEE TEVC, IEEE TCYB, IEEE TIM, IEEE TETCI, IEEE IOTJ, etc. He was the recipient of outstanding paper award from Computer Academy of Guangdong and the outstanding reviewer award of EJOR.

Prof. Xiao Zhang received the B.Eng. and M.Eng. degrees from South-Central Minzu University, Wuhan, China, in 2009 and 2011, respectively. In 2015, he was a visiting scholar with the Utah State University, Utah, USA. He received his Ph.D. degree from Department of Computer Science in City University of Hong Kong, Hong Kong, 2016. During 2016–2019, he was a postdoc research fellow at Singapore University of Technology and Design. Currently, he is an associate professor with College of Computer Science, South-Central Minzu University, China. His research interests include algorithms design and analysis, combinatorial optimization, wireless and UAV networking.

Prof. Sam Kwong is the chair professor of Computational Intelligence and concurrently as associate vice-president (Strategic Research) of Lingnan University. Professor Kwong is a distinguished scholar in evolutionary computation, artificial intelligence (AI) solutions and image/video processing, with a strong record of scientific innovations and real-world impacts. Professor Kwong was listed as one of the top 2% of the world’s most cited scientists, according to the Stanford University report. He was listed as one of the top 1% of the world’s most cited scientists by Clarivate in 2022. He has also been actively engaged in knowledge transfer  between academia and industry. He was elevated to IEEE Fellow in 2014 for his contributions to optimization techniques in cybernetics and video coding.

Relaterte produkter