A General Framework For Task-Oriented Network Inference

Abstract

We present a brief introduction to a flexible, general network inference framework which models data as a network space, sampled to optimize network structure to a particular task. We introduce a formal problem statement related to influence maximization in networks, where the network structure is not given as input, but learned jointly with an influence maximization solution.

SIAM SDM Workshop on Inferring Networks from Non-Network Data, 2017