Add to ORKGIn this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almost random generation, as described by Sinclair (1993). We give a RNC almost uniform generator for perfect matchings in dense bipartite graphs, and its RNC reduction to its counting problem. As a consequence we can classify the problem of getting an approximation scheme to the permanent of a boolean matrix in RNC. We also state other problems for which the same technique applies
AbstractThe paper studies effective approximate solutions to combinatorial counting and unform gener...
Abstract: "In this paper, the parallel complexity of the Random Matching Problem-a problem of genera...
We present a technique for converting RNC algorithms into NC algorithms. Our approach is based on a ...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
We give a RNC algorithm to sample matchings from a distribution on the set of matchings in a graph. ...
In the first part of this work, we present an RNC uniform generator of matchings of any size in a gr...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
AbstractThe paper studies effective approximate solutions to combinatorial counting and unform gener...
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For exam...
The paper studies effective approximate solutions to combinatorial counting and uniform generation p...
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For exam...
AbstractThe paper studies effective approximate solutions to combinatorial counting and unform gener...
Abstract: "In this paper, the parallel complexity of the Random Matching Problem-a problem of genera...
We present a technique for converting RNC algorithms into NC algorithms. Our approach is based on a ...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
We give a RNC algorithm to sample matchings from a distribution on the set of matchings in a graph. ...
In the first part of this work, we present an RNC uniform generator of matchings of any size in a gr...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
In this work we look into the parallelization (in the NC sense) of the Markov Chain approach to almo...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
AbstractThe paper studies effective approximate solutions to combinatorial counting and unform gener...
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For exam...
The paper studies effective approximate solutions to combinatorial counting and uniform generation p...
We describe several RNC algorithms for generating graphs and subgraphs uniformly at random. For exam...
AbstractThe paper studies effective approximate solutions to combinatorial counting and unform gener...
Abstract: "In this paper, the parallel complexity of the Random Matching Problem-a problem of genera...
We present a technique for converting RNC algorithms into NC algorithms. Our approach is based on a ...