The course presents continuous optimization techniques that have been developed to deal with the increasing amount of data. In particular; we look at optimization problems that depend on large-scale datasets; spatially distributed data; as well as local private data. We will focus on three different aspects: (1) the development of algorithms to decompose the problem into smaller problems that can be solved with some degree of coordination; (2) the trade- off of cooperation vs. local computation; (3) how to design algorithms that ensure privacy of sensitive data. This course is open to students of the M2 'Data Sciences'.
