In this article, we consider a class of submodular maximization problems in which decision-
makers have limited access to the objective function. We explore scenarios where the …

This article considers a set of sensors, which, as a group, are tasked with taking
measurements of the environment and sending a small subset of the measurements to a …

We consider a class of submodular maximization problems in which decision-makers have
limited access to the objective function. We explore scenarios where the decision-maker has …

We present a method to realize a submodular function as a vector in the feasible region of a
set of linear constraints. We utilize this representation to formulate a linear program to find …

Presented here is research focused on numerical advancements in Hamilton-Jacobi (HJ)
theory as they provide a fundamental tool to address many problems in autonomous …

In general, submodular maximization is relevant in many problems in controls, robotics and
machine learning, because it models many computationally difficult problems. A simple …