AbstractIn this work we present a fully randomized approximation scheme for counting the number of perfect matchings in a dense bipartite graphs, that is equivalent to get a fully randomized approximation scheme to the permanent of a dense boolean matrix. We achieve this known solution, through novel extensions in the theory of suitable non-reversible, Markov chains which mix rapidly and have a near-uniform distribution
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
Abstract. We look at the minimal size of a maximal matching in general, bipartite and ¡-regular rand...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
<p>We develop algorithms to approximately count perfect matchings in bipartite graphs (or permanents...
We investigate efficient randomized methods for approximating the number of perfect matchings in bip...
We investigate efficient randomized methods for approximating the number of perfect matchings in bip...
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 the first part of this work, we present an RNC uniform generator of matchings of any size in a gr...
We give a RNC algorithm to sample matchings from a distribution on the set of matchings in a graph. ...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
Abstract. We look at the minimal size of a maximal matching in general, bipartite and ¡-regular rand...
AbstractIn this work we present a fully randomized approximation scheme for counting the number of p...
<p>We develop algorithms to approximately count perfect matchings in bipartite graphs (or permanents...
We investigate efficient randomized methods for approximating the number of perfect matchings in bip...
We investigate efficient randomized methods for approximating the number of perfect matchings in bip...
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 the first part of this work, we present an RNC uniform generator of matchings of any size in a gr...
We give a RNC algorithm to sample matchings from a distribution on the set of matchings in a graph. ...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
International audienceWe investigate efficient randomized methods for approximating the number of pe...
Abstract. We look at the minimal size of a maximal matching in general, bipartite and ¡-regular rand...