In this paper, we propose a stochastic scheduling strategy for estimating the states of N
discrete-time linear time invariant (DTLTI) dynamic systems, where only one system can be …

Consider the problem of choosing a string of actions to optimize an objective function that is
string submodular. It was shown in previous papers that the greedy strategy, consisting of a …

Motivated by applications in online advertising, we consider a class of maximization
problems where the objective is a function of the sequence of actions and the running …

Submodular maximization has been the backbone of many important machine-learning
problems, and has applications to viral marketing, diversification, sensor placement, and …

Submodularity is an important property of set functions and has been extensively studied in
the literature. It models set functions that exhibit a diminishing returns property, where the …

We study the problem of controlling multiple 2-D directional sensors while maximizing an
objective function based on the information gain corresponding to multiple target locations …

We study a social network consisting of agents organized as a hierarchical M-ary rooted
tree, common in enterprise and military organizational structures. The goal is to aggregate …

The problem of choosing a string of actions to optimize an objective function that is string
submodular has been considered in [1]. There it is shown that the greedy strategy …

We propose a centralized radix-2 multistage decision fusion strategy comprising simple
AND and OR rules for cooperative spectrum sensing in cognitive sensor networks. Earlier …

We study the distributed detection problem in a balanced binary relay tree, where the leaves
of the tree are sensors generating binary messages. The root of the tree is a fusion center …