Large-Scale Convex Optimization: Algorithms & Analyses Via Monotone Operators Ryu Ernest K.

Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods - including parallel-distributed algorithms - through the abstraction of monotone operators. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved.

Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms.