I. Introduction
Graph signal processing is an emerging field that studies multidimensional signals embedded in a graph which represents the inherent relationship among the different entities [1]. Graph signal processing has attracted an increased attention as it allows us to capture complex correlations in many practical problems. Thus, it has been readily applied for various problems consisting of signal recovery, prediction, and anomaly detection [2]. Recently, much work has been devoted to graph sampling, which studies recovery of entire graph signal using observations at only some of the nodes [3]–[8].