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Marek Karpinski

Known as: Karpinski 
Marek Karpinski is a computer scientist and mathematician known for his research in the theory of algorithms and their applications, combinatorial… 
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17 relations
APXAlgorithmApproximation algorithmCombinatorial optimization

Papers overview

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2013
2013
Efficient Clause Learning for Quantified Boolean Formulas via QBF Pseudo Unit Propagation
Recent solvers for quantified boolean formulas (QBF) use a clause learning method based on a procedure proposed by Giunchiglia et… 
Highly Cited
2007
Highly Cited
2007
On the predictive validity of indirect attitude measures: Prediction of consumer choice behavior on the basis of affective priming in the picture–picture naming task
Highly Cited
2007
Highly Cited
2007
The influence of stereotypes on decisions to shoot
Using a videogame to simulate encounters with potentially hostile targets, three studies tested a model in which racial bias in… 
2005
2005
Approximating vertex cover on dense graphs
Although many problems in MAX-SNP admit a PTAS for dense graphs, that is not the case for Vertex Cover, which is MAX-SNP hard… 
Highly Cited
2003
Highly Cited
2003
Random sampling and approximation of MAX-CSPs
Highly Cited
1999
Highly Cited
1999
A 1.598 approximation algorithm for the Steiner problem in graphs
We present a general iterative framework for improving the performance ratio of Steiner tree approximation algorithms. By… 
Highly Cited
1991
Highly Cited
1991
Hadron calorimetry in the L3 detector
1990
1990
Computational Complexity of Learning Read-Once Formulas over Different Bases
We study computational complexity of learning read-once formulas over different boolean bases. In particular we design a… 
Highly Cited
1989
Highly Cited
1989
Complexity-Theoretic Aspects of Interactive Proof Systems
In 1985, Goldwasser, Micali and Racko formulated interactive proof systems as a tool for developing cryptographic protocols… 
Highly Cited
1988
Highly Cited
1988
Fast Parallel Algorithms for Sparse Multivariate Polynomial Interpolation over Finite Fields
The authors consider the problem of reconstructing (i.e., interpolating) a t-sparse multivariate polynomial given a black box… 
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