3 accepted papers
In numerous graph signal processing applications, data is often missing for a variety of reasons, and predicting the missing data is essential. In this paper, we consider data on graphs modeled as bandlimited graph signals. Predicting or reconstructing the unknown signal values for such a model requ…
This paper considers the graph signal sampling problem when some of the selected samples are lost or unavailable due to sensor failures or adversarial erasures. We formulate a robust graph signal sampling problem where only a subset of selected samples are received, and the goal is to maximize the w…
We consider the problem of sampling signals defined on the nodes of a graph. This problem arises in many contexts where the data is not structured and needs to be reconstructed from a few samples. While other graph signal sampling techniques have been recently developed in the literature, these are…