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Fixed Point Optimization Algorithms and Their Applications
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Fixed Point Optimization Algorithms and Their Applications discusses how the relationship between fixed point algorithms and optimization problems is connected and demonstrates hands-on applications of the algorithms in fields such as image restoration, signal recovery, and machine learning. The author presents algorithms for non-expansive and generalized non-expansive mappings in Hilbert space, and includes solutions to many optimization problems across a range of scientific research and real-world applications. From foundational concepts, the book proceeds to present a variety of optimization algorithms, including fixed point theories, convergence theorems, variational inequality problems, minimization problems, split feasibility problems, variational inclusion problems, and equilibrium problems.
This book will equip readers with the theoretical mathematics background and necessary tools to tackle challenging optimization problems involving a range of algebraic methods, empowering them to apply these techniques in their research, professional work, or academic pursuits.Cholamjiak, Watcharaporn: -
Dr. Watcharaporn Cholamjiak serves as an Associate Professor of Mathematics at the University of Phayao's School of Science in Thailand. She earned both her MSc and PhD in Mathematics from Chiang Mai University, under the guidance of Professor Suthep Suantai. Dr. Cholamjiak has an established collaboration with Professor Yeal Je Cho at Gyeongsang National University in Chinju, Korea, and has published numerous papers in highly regarded international journals. Her research has recently pivoted to the development of optimization algorithms for image restoration and signal recovery, areas in which she has produced significant published work. She is also a dedicated staff member of the Unit of Excellence in Image Recovery and Analysis and currently leads the Unit of Excellence in Data Analytics at the University of Phayao, focusing her research on the application of optimization algorithms in machine learning.
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