<div class="csl-bib-body">
<div class="csl-entry">Brand, C. (2022). Discriminantal subset convolution: Refining exterior-algebraic methods for parameterized algorithms. <i>Journal of Computer and System Sciences</i>, <i>129</i>, 62–71. https://doi.org/10.1016/j.jcss.2022.05.004</div>
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dc.identifier.issn
0022-0000
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/142165
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dc.description.abstract
We give a simplified account of the recent algebraic methods obtained for the longest path problem of Brand, Dell and Husfeldt (STOC'18) and Brand (ESA'19). To this end, we introduce a new kind of subset convolution, discriminantal subset convolution, which we motivate as a distillate of exterior-algebraic operations. The algorithm in the new presentation achieves the almost competitive bound of 2.619k⋅poly(n), first achieved by Fomin et al. (2016) [8], for deterministically finding paths of length k, while it allows for the same running time for the k-internal out-branching problem, improving upon Brand (ESA'19) and reproducing the state-of-the-art of Brand and Pratt (ICALP'21).
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dc.language.iso
en
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dc.publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
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dc.relation.ispartof
Journal of Computer and System Sciences
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dc.subject
Algebraic algorithms
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dc.subject
Extensor coding
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dc.subject
Fast subset convolution
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dc.subject
Longest path problem
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dc.subject
Parameterized algorithms
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dc.title
Discriminantal subset convolution: Refining exterior-algebraic methods for parameterized algorithms