In this paper we give an introduction to the connection between complexity theory and the study of randomized algorithms. In particular, we will define and study probabilistic complexity classes, survey the basic results, and show how they relate to the notion of randomized algorithms
This document contains lecture notes of an introductory course on Kolmogorov complexity. They cover ...
This paper offers some new results on randomness with respect to classes of measures, along with a d...
AbstractGeneral properties and proof techniques concerning probabilistic complexity classes are disc...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
By flipping a coin repeatedly and recording the result, we can create a sequence that intuitively is...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
AbstractResearch conducted over the past fifteen years has amply demonstrated the advantages of algo...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
Abstract: We study a time bounded variant of Kolmogorov complexity. This motion, together with unive...
Randomness can help to solve problems and is a fundamental ingredient and tool in modern com-plexity...
Introduction We have already seen some uses of randomization in the design of on-line algorithms. I...
In this paper we apply some elementary computability-theoretic notions to algorithmic complexity the...
In this dissertation we consider two different notions of randomness and their applications to probl...
UnrestrictedAn algorithm can be defined as a set of computational steps that transform the input to ...
This document contains lecture notes of an introductory course on Kolmogorov complexity. They cover ...
This paper offers some new results on randomness with respect to classes of measures, along with a d...
AbstractGeneral properties and proof techniques concerning probabilistic complexity classes are disc...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
By flipping a coin repeatedly and recording the result, we can create a sequence that intuitively is...
Random number generators are widely used in practical algorithms. Examples include simulation, numbe...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
AbstractResearch conducted over the past fifteen years has amply demonstrated the advantages of algo...
I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, ...
Abstract: We study a time bounded variant of Kolmogorov complexity. This motion, together with unive...
Randomness can help to solve problems and is a fundamental ingredient and tool in modern com-plexity...
Introduction We have already seen some uses of randomization in the design of on-line algorithms. I...
In this paper we apply some elementary computability-theoretic notions to algorithmic complexity the...
In this dissertation we consider two different notions of randomness and their applications to probl...
UnrestrictedAn algorithm can be defined as a set of computational steps that transform the input to ...
This document contains lecture notes of an introductory course on Kolmogorov complexity. They cover ...
This paper offers some new results on randomness with respect to classes of measures, along with a d...
AbstractGeneral properties and proof techniques concerning probabilistic complexity classes are disc...
DOI
Add to ORKG