Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Non-monotone DR-Submodular Function Maximization   We consider non-monotone DR-submodular function maximization, where
DR-submodularity (diminishing return submodularity) is an extension of
submodularity for functions over the integer lattice based on the concept of
the diminishing return property. Maximizing non-monotone DR-submodular
functions has many applications in machine learning that cannot be captured by
submodular set functions. In this paper, we present a
$\frac{1}{2+\epsilon}$-approximation algorithm with a running time of roughly
$O(\frac{n}{\epsilon}\log^2 B)$, where $n$ is the size of the ground set, $B$
is the maximum value of a coordinate, and $\epsilon > 0$ is a parameter. The
approximation ratio is almost tight and the dependency of running time on $B$
is exponentially smaller than the naive greedy algorithm. Experiments on
synthetic and real-world datasets demonstrate that our algorithm outputs almost
the best solution compared to other baseline algorithms, whereas its running
time is several orders of magnitude faster.

27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ