Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive Maximization of Pointwise Submodular Functions With Budget
  Constraint   We study the worst-case adaptive optimization problem with budget constraint
that is useful for modeling various practical applications in artificial
intelligence and machine learning. We investigate the near-optimality of greedy
algorithms for this problem with both modular and non-modular cost functions.
In both cases, we prove that two simple greedy algorithms are not near-optimal
but the best between them is near-optimal if the utility function satisfies
pointwise submodularity and pointwise cost-sensitive submodularity
respectively. This implies a combined algorithm that is near-optimal with
respect to the optimal algorithm that uses half of the budget. We discuss
applications of our theoretical results and also report experiments comparing
the greedy algorithms on the active learning problem.

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The categories of this paper are: hep-ph
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph