Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computational Aspects of Conditional Minisum Approval Voting in
  Elections with Interdependent Issues   Approval voting provides a simple, practical framework for multi-issue
elections, and the most representative example among such election rules is the
classic Minisum approval voting rule. We consider a generalization of Minisum,
introduced by the work of Barrot and Lang [2016], referred to as Conditional
Minisum, where voters are also allowed to express dependencies between issues.
The price we have to pay when we move to this higher level of expressiveness is
that we end up with a computationally hard rule. Motivated by this, we focus on
the computational aspects of Conditional Minisum, where progress has been
rather scarce so far. We identify restrictions that concern the voters'
dependencies and the value of an optimal solution, under which we provide the
first multiplicative approximation algorithms for the problem. At the same
time, by additionally requiring certain structural properties for the union of
dependencies cast by the whole electorate, we obtain optimal efficient
algorithms for well-motivated special cases. Overall, our work provides a
better understanding on the complexity implications introduced by conditional
voting.

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The categories of this paper are: eess
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
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The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
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The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
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The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
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The categories of this paper are: q-bio
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The categories of this paper are: acc-phys
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The categories of this paper are: ao-sci