The aim of the workshop is to  provide a concise, yet complete, exposition to the topic of distributed and stochastic optimization, with an in depth understanding of the mathematical and algorithmic mechanisms underlying it, of the potential communication and computational savings of such implementations, and of how uncertainty can be dealt with in a rigorous manner. This comprehensive introduction to the machinery underlying distributed and stochastic optimization will  encourage the development of new results and the investigation of several important issues in the future of distributed optimization and control over uncertain networks, possibly through novel collaborations.

Merging distributed optimization algorithms with stochastic optimization techniques that allow for a rigorous treatment of uncertainty is a quite challenging problem.

We believe that this full-day workshop will help building the appropriate background to address it, by demonstrating recent advances on the broad topic of distributed and stochastic optimization, offering attendees the opportunity to get exposed to recent algorithmic developments as well as to applications of contemporary interest like smart grid  monitoring and control, control of cyber-physical systems, and wireless networks.

The workshop brings together a diverse group of internationally recognized researchers, who are affiliated with outstanding institutions in Europe and in the United States. Attendees will be exposed to cutting edge research on the field, acquire a comprehensive awareness of the literature, and get some insight on the potential connections and complementarities among different algorithmic alternatives as well as new vistas on the field.