Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text 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.

This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. An extensive general Introduction places the Novelas in the context of Cervantes's life and work; provides basic information about their content, composition, internal ordering, publication, and critical reception, gives detailed consideration to the contemporary literary-theoretical issues implicit in the title, and outlines and...

This edited volume of fourteen specially commissioned essays written from a variety of critical perspectives by leading cervantine scholars seeks to provide an overview of Cervantes's Novelas ejemplares which will be of interest to a broad academic readership. An extensive general Introduction places the Novelas in the context of Cervantes's life and work; provides basic information about their content, composition, internal ordering, publication, and critical reception, gives detailed consideration to the contemporary literary-theoretical issues implicit in the title, and outlines and...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features or training examples. As a result, both the decentralized collection or storage of these datasets as well as accompanying distributed solution methods are either necessary or at least highly desirable. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers argues that...

The corpus of literary works shaped by the Renaissance and the Baroque that appeared in Spain during the sixteenth and seventeenth centuries had a transforming effect on writing throughout Europe and left a rich legacy that scholars continue to explore. For four decades after the Spanish Civil War the study of this literature flourished in Great Britain and Ireland, where many of the leading scholars in the field were based. Though this particular 'Golden Age' was followed by a decline for many years, there have recently been signs of a significant revival. The present book seeks to showcase...

Performance Bounds and Suboptimal Policies for Multi-Period Investment examines dynamic trading of a portfolio of assets in discrete periods over a finite time horizon, with arbitrary time-varying distribution of asset returns. The goal is to maximize the total expected revenue from the portfolio, while respecting constraints on the portfolio like a required terminal portfolio and leverage and risk limits. The revenue takes into account the gross cash generated in trades, transaction costs, and costs associated with the positions, such as fees for holding short positions. The model that is...

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.