Cooperative Optimization for Data Science
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.