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 allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined

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

"Fixed-Point Algorithms for Inverse Problems in Science and Engineering" presents some of the most recent work from top-notch researchers studying projection an

Because they incorporate both time- and event-driven dynamics, stochastic hybrid systems (SHS) have become ubiquitous in a variety of fields, from mathematical