Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.
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反过来,我们可以将罚函数逼近问题 minimize \sum_{i=1}^{m}\phi (b_{i}-a_{i}^Tx ) 理解为最大似然估计问题,其中噪声概率密度为 p(z)=\frac{e^{-\phi(z)}}{\int e^{-\phi(u)du}} 测量值为b
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