Optimization from samples

Abstract

Optimization from samples studies how one can optimize objective functions from the sample data that one uses to learn them.Firstly, the mathematical model of this problem-optimization from samples model, as well as the inapproximability results under this model, was introduced.Secondly, some approaches and variants of OPS were introduced, in order to circumvent the impossibility results and make optimization possible.Thirdly, one of the variants-the optimization from structured samples model was focused on, and the algorithms for maximum coverage and influence maximization problem under it were introduced in details.Finally, the paper was concluded, and some future research directions for the problem were proposed.

Keywords

• optimization from samples;data-driven optimization;structured sample;maximum coverage problem;influence maximization problem