activity
19992020
most citedFaster Algorithms for Feedback Arc Set Tournament, Kemeny Rank Aggregation and Betweenness Tournament

22 citations · 138 across the 41 of their papers we have counts for

collaborators

52 papers

math.NT2020

Noisy polynomial interpolation modulo prime powers

Marek Karpinski, Igor Shparlinski

We consider the {\it noisy polynomial interpolation problem\/} of recovering an unknown -sparse polynomial over the ring of residues modulo , where…

cs.DS2020

Dense Steiner problems: Approximation algorithms and inapproximability

Marek Karpinski, Mateusz Lewandowski, Syed Mohammad Meesum +1

The Steiner Tree problem is a classical problem in combinatorial optimization: the goal is to connect a set of terminals in a graph by a tree of minimum size. Karpinski and…

cs.CC2017

Identity Testing and Interpolation from High Powers of Polynomials of Large Degree over Finite Fields

Marek Karpinski, Laszlo Mérai, Igor E. Shparlinski

We consider the problem of identity testing and recovering (that is, interpolating) of a "hidden" monic polynomials , given an oracle access to for , w…

cs.DS2016

Approximation Complexity of Max-Cut on Power Law Graphs

Mikael Gast, Mathias Hauptmann, Marek Karpinski

In this paper we study the MAX-CUT problem on power law graphs (PLGs) with power law exponent . We prove some new approximability results on that problem. In particular we show…

cs.CC2015★ 13 cited

Effect of Gromov-hyperbolicity Parameter on Cuts and Expansions in Graphs and Some Algorithmic Implications

Bhaskar DasGupta, Marek Karpinski, Nasim Mobasheri +1

-hyperbolic graphs, originally conceived by Gromov in 1987, occur often in many network applications; for fixed , such graphs are simply called hyperbolic graphs and include…

cs.DS2015

Approximability of TSP on Power Law Graphs

Mikael Gast, Mathias Hauptmann, Marek Karpinski

In this paper we study the special case of Graphic TSP where the underlying graph is a power law graph (PLG). We give a refined analysis of some of the current best approximation a…