The age of Big Data is here: data of huge sizes is becoming ubiquitous. With this comes the need to solve optimization problems of unprecedented sizes. Machine learning, compressed sensing, social network science and computational biology are some of many prominent application domains where it is easy to formulate optimization problems with millions or billions of variables. Classical optimization algorithms are not designed to scale to instances of this size; new approaches are needed. This workshop aims to bring together researchers working on novel optimization algorithms and codes capable of working in the Big Data setting.
For further details, see the workshop website