• Medientyp: E-Artikel; Sonstige Veröffentlichung; Elektronischer Konferenzbericht
  • Titel: Certified Algorithms: Worst-Case Analysis and Beyond
  • Beteiligte: Makarychev, Konstantin [VerfasserIn]; Makarychev, Yury [VerfasserIn]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2020
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/LIPIcs.ITCS.2020.49
  • Schlagwörter: Bilu ; integrality ; beyond-worst-case analysis ; Linial stability ; perturbation resilience ; approximation algorithm ; certified algorithm
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  • Beschreibung: In this paper, we introduce the notion of a certified algorithm. Certified algorithms provide worst-case and beyond-worst-case performance guarantees. First, a γ-certified algorithm is also a γ-approximation algorithm - it finds a γ-approximation no matter what the input is. Second, it exactly solves γ-perturbation-resilient instances (γ-perturbation-resilient instances model real-life instances). Additionally, certified algorithms have a number of other desirable properties: they solve both maximization and minimization versions of a problem (e.g. Max Cut and Min Uncut), solve weakly perturbation-resilient instances, and solve optimization problems with hard constraints. In the paper, we define certified algorithms, describe their properties, present a framework for designing certified algorithms, provide examples of certified algorithms for Max Cut/Min Uncut, Minimum Multiway Cut, k-medians and k-means. We also present some negative results.
  • Zugangsstatus: Freier Zugang