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An R package for permutations, Mallows and Generalized Mallows models
(2014-01-22)
[EN]Probability models on permutations associate a probability value to each of the permutations on n items. This paper considers two popular probability models, the Mallows model and the Generalized Mallows model. We ...
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony
(2010)
Haplotype data is especially important in the study of complex diseases
since it contains more information than genotype data. However,
obtaining haplotype data is technically difficult and expensive. Computational
methods ...
Sampling and learning the Mallows and Generalized Mallows models under the Cayley distance
(2014-01-22)
[EN]The Mallows and Generalized Mallows models are compact yet powerful and natural ways of representing a probability distribution over the space of permutations. In this paper we deal with the problems of sampling and ...
Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance
(2014-01-22)
[EN]In this paper we deal with distributions over permutation spaces. The Mallows model is the mode l in use. The associated distance for permutations is the Hamming distance.
Sampling and learning the Mallows model under the Ulam distance
(2014-01-22)
[EN]In this paper we deal with probability distributions over permutation spaces. The Probability model in use is the Mallows model. The distance for permutations that the model uses in the Ulam distance.
Learning Probability Distributions over Permutations by Means of Fourier Coefficients
(2011)
A large and increasing number of data mining domains consider data
that can be represented as permutations. Therefore, it is important to
devise new methods to learn predictive models over datasets of permutations.
However, ...
A review on Estimation of Distribution Algorithms in Permutation-based Combinatorial Optimization Problems
(2011)
Estimation of Distribution Algorithms (EDAs) are a set of algorithms
that belong to the field of Evolutionary Computation. Characterized by the use of
probabilistic models to represent the solutions and the dependencies ...
Extending Distance-based Ranking Models In Estimation of Distribution Algorithms
(2014-05-20)
Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking ...