Introduction to Online Convex Optimization

<p><em>Introduction to </em><em>Online Convex Optimization</em> portrays optimization as a process. In many practical applications the environment is so complex that it is infeasible to lay out a comprehensive theoretical model and use classical algorithmic theory and mathematical optimization. It is necessary as well as beneficial to take a robust approach by applying an optimization method that learns as one goes along learning from experience as more aspects of the problem are observed. This view of optimization as a process has become prominent in varied fields and has led to some spectacular success in modeling and systems that are now part of our daily lives.</p><p><em>Introduction to </em><em>Online Convex Optimization</em> is intended to serve as a reference for a self-contained course on online convex optimization and the convex optimization approach to machine learning for the educated graduate student in computer science/electrical engineering/ operations research/statistics and related fields. It is also an ideal reference for the researcher diving into this fascinating world at the intersection of optimization and machine learning.</p>