Abstract—We study the rate-distortion relationship in the set of permutations endowed with the Kendall τ-metric and the Chebyshev metric. Our study is motivated by the application of permutation rate-distortion to the average-case and worst-case distortion analysis of algorithms for ranking with incomplete information and approximate sorting algorithms. For the Kendall τ-metric we provide bounds for small, medium, and large distortion regimes, while for the Chebyshev metric we present bounds that are valid for all distortions and are especially accurate for small distortions. In addition, for the Chebyshev metric, we provide a construction for covering codes. I
Abstract — Classical rate-distortion theory requires knowledge of an elusive source distribution. In...
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or expla...
International audienceThe topic of the article is the parametric study of the complexity of algorith...
We study the rate-distortion relationship in the set of permutations endowed with the Kendall t-metr...
We study the rate-distortion relationship in the set of permutations endowed with the Kendall Tau me...
Abstract—We investigate the lossy compression of per-mutations by analyzing the trade-off between th...
We investigate lossy compression (source coding) of data in the form of permutations. This problem h...
We investigate the lossy compression of the permutation space by analyzing the trade-off between the...
In this paper, we investigate the problem of compression of data that are in the form of permutation...
We examine the structure of families of distortion balls from the perspective of Kolmogorov complexi...
We consider the problem of approximate sorting of a data stream (in one pass) with limited internal ...
We consider the problem of approximate sorting of a data stream (in one pass) with limited internal ...
A measure of association between two rankings is proposed. This measure -- the maximum of the absolu...
Abstract—Classical rate-distortion theory requires specifying a source distribution. Instead, we ana...
Classical rate-distortion theory requires specifying a source distribution. Instead, we analyze rate...
Abstract — Classical rate-distortion theory requires knowledge of an elusive source distribution. In...
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or expla...
International audienceThe topic of the article is the parametric study of the complexity of algorith...
We study the rate-distortion relationship in the set of permutations endowed with the Kendall t-metr...
We study the rate-distortion relationship in the set of permutations endowed with the Kendall Tau me...
Abstract—We investigate the lossy compression of per-mutations by analyzing the trade-off between th...
We investigate lossy compression (source coding) of data in the form of permutations. This problem h...
We investigate the lossy compression of the permutation space by analyzing the trade-off between the...
In this paper, we investigate the problem of compression of data that are in the form of permutation...
We examine the structure of families of distortion balls from the perspective of Kolmogorov complexi...
We consider the problem of approximate sorting of a data stream (in one pass) with limited internal ...
We consider the problem of approximate sorting of a data stream (in one pass) with limited internal ...
A measure of association between two rankings is proposed. This measure -- the maximum of the absolu...
Abstract—Classical rate-distortion theory requires specifying a source distribution. Instead, we ana...
Classical rate-distortion theory requires specifying a source distribution. Instead, we analyze rate...
Abstract — Classical rate-distortion theory requires knowledge of an elusive source distribution. In...
Statistics is a mathematical science pertaining to the collection, analysis, interpretation or expla...
International audienceThe topic of the article is the parametric study of the complexity of algorith...