Information science Convex analysis and optimization theory

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Information Science
A reference book that explains the mathematics of convex analysis and nonlinear optimization in an easy-to-understand way. This book explains the mathematics of convex analysis and nonlinear optimization (nonlinear planning) on an n-dimensional Euclidean space from the basics in an easy-to-understand way. The mathematics of convex analysis and nonlinear optimization is the background of the techniques used in regression analysis and machine learning (supervised learning). This book includes detailed proofs of many propositions and theorems, touches on エークランド's theorem and fixed point theorem, which are widely applied, and is designed to be easy to read by science and engineering and economics students and researchers. In addition, at the end of the book, there is an appendix that summarizes the contents of differential and integral and linear algebra necessary for understanding the text, and detailed explanations of exercise questions at the end of each chapter to enhance the convenience of readers. * This book is published by Ohm Co., Ltd. based on the book published by Makino Shoten.