Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Improved Greedy Algorithm for Subset Selection in Linear Estimation   In this paper, we consider a subset selection problem in a spatial field
where we seek to find a set of k locations whose observations provide the best
estimate of the field value at a finite set of prediction locations. The
measurements can be taken at any location in the continuous field, and the
covariance between the field values at different points is given by the widely
used squared exponential covariance function. One approach for observation
selection is to perform a grid discretization of the space and obtain an
approximate solution using the greedy algorithm. The solution quality improves
with a finer grid resolution but at the cost of increased computation. We
propose a method to reduce the computational complexity, or conversely to
increase solution quality, of the greedy algorithm by considering a search
space consisting only of prediction locations and centroids of cliques formed
by the prediction locations. We demonstrate the effectiveness of our proposed
approach in simulation, both in terms of solution quality and runtime.

19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys