作者:Tzoumas, Vasileios; Jadbabaie, Ali; Pappas, George J.
作者单位:University of Michigan System; University of Michigan; Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); University of Pennsylvania
摘要:Emerging applications of control, estimation, and machine learning, from target tracking to decentralized model fitting, pose resource constraints that limit which of the available sensors, actuators, or data can be simultaneously used across time. Therefore, many researchers have proposed solutions within discrete optimization frameworks where the optimization is performed over finite sets. By exploiting notions of discrete convexity, such as submodularity, the researchers have been able to p...