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Approximate counting of K-paths : Deterministic and in polynomial space

Björklund, Andreas (författare)
Lund University,Lunds universitet,Institutionen för datavetenskap,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Computer Science,Departments at LTH,Faculty of Engineering, LTH
Lokshtanov, Daniel (författare)
University of California, Santa Barbara
Saurabh, Saket (författare)
The Institute of Mathematical Sciences
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Zehavi, Meirav (författare)
Ben Gurion University of the Negev
Chatzigiannakis, Ioannis (redaktör/utgivare)
Baier, Christel (redaktör/utgivare)
Leonardi, Stefano (redaktör/utgivare)
Flocchini, Paola (redaktör/utgivare)
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 (creator_code:org_t)
2019
2019
Engelska.
Ingår i: 46th International Colloquium on Automata, Languages, and Programming, ICALP 2019. - 9783959771092 ; 132
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
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  • A few years ago, Alon et al. [ISMB 2008] gave a simple randomized O((2e)km∊−2)-time exponential-space algorithm to approximately compute the number of paths on k vertices in a graph G up to a multiplicative error of 1 ± ∊. Shortly afterwards, Alon and Gutner [IWPEC 2009, TALG 2010] gave a deterministic exponential-space algorithm with running time (2e)k+O(log3 k)m log n whenever ∊−1 = kO(1). Recently, Brand et al. [STOC 2018] provided a speed-up at the cost of reintroducing randomization. Specifically, they gave a randomized O(4km∊−2)-time exponential-space algorithm. In this article, we revisit the algorithm by Alon and Gutner. We modify the foundation of their work, and with a novel twist, obtain the following results. We present a deterministic 4k+O(√k(log2 k+log2 ∊−1))m log n-time polynomial-space algorithm. This matches the running time of the best known deterministic polynomial-space algorithm for deciding whether a given graph G has a path on k vertices. Additionally, we present a randomized 4k+O(log k(log k+log ∊−1))m log n-time polynomial-space algorithm. While Brand et al. make non-trivial use of exterior algebra, our algorithm is very simple; we only make elementary use of the probabilistic method. Thus, the algorithm by Brand et al. runs in time 4k+o(k)m whenever ∊−1 = 2o(k), while our deterministic and randomized algorithms run in time 4k+o(k)m log n whenever ∊−1 = 2o(k 4 ) and 1 ∊−1 = 2o(log k k ), respectively. Prior to our work, no 2O(k)nO(1)-time polynomial-space algorithm was known. Additionally, our approach is embeddable in the classic framework of divide-and-color, hence it immediately extends to approximate counting of graphs of bounded treewidth; in comparison, Brand et al. note that their approach is limited to graphs of bounded pathwidth.

Ämnesord

NATURVETENSKAP  -- Matematik -- Diskret matematik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Discrete Mathematics (hsv//eng)

Nyckelord

Approximate counting
K-Path
Parameterized complexity

Publikations- och innehållstyp

kon (ämneskategori)
ref (ämneskategori)

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