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This book focuses on the applications of convex optimization. It will help the reader learn how to recognize and formulate convex optimization problems that might be encountered in practice. Due to the width and depth of topics in convex optimization, it is impossible to provide a comprehensive overview of all of them in this book. Instead the author highlights several representative topics, including support vector machines, parameter estimation, norm approximation and regularization, semi-definite programming problems, convex relaxation and geometric problems. All derivation processes are presented in detail so that readers can teach themselves without difficulty.
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