Finding maximum matchings in random regular graphs in linear expected time. Issue 3 (24th November 2020)
- Record Type:
- Journal Article
- Title:
- Finding maximum matchings in random regular graphs in linear expected time. Issue 3 (24th November 2020)
- Main Title:
- Finding maximum matchings in random regular graphs in linear expected time
- Authors:
- Anastos, Michael
Frieze, Alan - Abstract:
- Abstract: In a seminal paper on finding large matchings in sparse random graphs, Karp and Sipser proposed two algorithms for this task. The second algorithm has been intensely studied, but due to technical difficulties, the first algorithm has received less attention. Empirical results by Karp and Sipser suggest that the first algorithm is superior. In this paper we show that this is indeed the case, at least for random k ‐regular graphs. We show that w.h.p. the first algorithm will find a matching of size n / 2 − O ( log n ) in a random k ‐regular graph, k = O (1). We also show that the algorithm can be adapted to find a maximum matching in O ( n ) time w.h.p. This is to be compared with O ( n 3/2 ) time for the worst‐case.
- Is Part Of:
- Random structures & algorithms. Volume 58:Issue 3(2021)
- Journal:
- Random structures & algorithms
- Issue:
- Volume 58:Issue 3(2021)
- Issue Display:
- Volume 58, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 58
- Issue:
- 3
- Issue Sort Value:
- 2021-0058-0003-0000
- Page Start:
- 390
- Page End:
- 429
- Publication Date:
- 2020-11-24
- Subjects:
- Karp‐Sipser Algorithm -- maximum matching -- random regular graph
Random graphs -- Periodicals
Mathematical analysis -- Periodicals
519 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-2418 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/rsa.20980 ↗
- Languages:
- English
- ISSNs:
- 1042-9832
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7254.411950
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16160.xml