Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Randomized Greedy Algorithm for Near-Optimal Sensor Scheduling in
  Large-Scale Sensor Networks   We study the problem of scheduling sensors in a resource-constrained linear
dynamical system, where the objective is to select a small subset of sensors
from a large network to perform the state estimation task. We formulate this
problem as the maximization of a monotone set function under a matroid
constraint. We propose a randomized greedy algorithm that is significantly
faster than state-of-the-art methods. By introducing the notion of curvature
which quantifies how close a function is to being submodular, we analyze the
performance of the proposed algorithm and find a bound on the expected mean
square error (MSE) of the estimator that uses the selected sensors in terms of
the optimal MSE. Moreover, we derive a probabilistic bound on the curvature for
the scenario where{\color{black}{ the measurements are i.i.d. random vectors
with bounded $\ell_2$ norm.}} Simulation results demonstrate efficacy of the
randomized greedy algorithm in a comparison with greedy and semidefinite
programming relaxation methods.

6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: hep-ex
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The categories of this paper are: adap-org
14
The categories of this paper are: math-ph