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Recent results on the total variation distance

2019
Let (X 1 ,...,X n ) and (Y 1 ,...,Y n ) be two sets of independent discrete random variables. Explicit upper and lower bounds for the total variation distance between distributions of these sets are obtained in terms of some functions of distributions of separate components X k and Y k , k = 1,...,n.
openaire   +1 more source

The Total Variation Distance for Comparing Non-Additive Measures

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
The Total Variation is a common distance between probability distributions that measures the maximum difference in probability among all events. When comparing non-additive measures, that can be represented by closed and convex sets of probability measures, the Total Variation distance can be extended in multiple ways.
David Nieto-Barba   +2 more
openaire   +1 more source

Total variation distance for discretely observed Lévy processes: A Gaussian approximation of the small jumps

Annales De L'institut Henri Poincare (B) Probability and Statistics, 2021
Alexandra Carpentier   +2 more
exaly  

Optimal Utility-Privacy Trade-Off With Total Variation Distance as a Privacy Measure

IEEE Transactions on Information Forensics and Security, 2020
Borzoo Rassouli, Deniz Gunduz
exaly  

A novel multi-objective immunization algorithm based on dynamic variation distance

Swarm and Evolutionary Computation, 2023
Junjiang He, Liming Wang, Bo Zeng
exaly  

Distance in Variation between Two Arbitrary Distributions via the Associated w-Functions

Theory of Probability and Its Applications, 1996
Nickos Papadatos, V Papathanasiou
exaly  

Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition

IEEE Transactions on Image Processing, 2013
Quanxue Gao, Feifei Gao, Hailin Zhang
exaly  

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