Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine l

Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type of optimization problem, a

This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learnin

Proximal Algorithms discusses proximal operators and proximal algorithms, and illustrates their applicability to standard and distributed convex optimization in

This volume contains thirteen articles on advances in applied mathematics and computing methods for engineering problems. Six papers are on optimization methods