Results 11 to 20 of about 2,328,427 (283)
Trends to Equilibrium in Total Variation Distance [PDF]
Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 2007 This paper presents different approaches, based on functional inequalities, to study the speed of convergence in total variation distance of ergodic diffusion processes with initial law satisfying a given integrability condition.
Cattiaux, Patrick, Guillin, Arnaud
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On Approximating Total Variation Distance
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Total variation distance (TV distance) is a fundamental notion of distance between probability distributions. In this work, we introduce and study the problem of computing the TV distance of two product distributions over the domain {0,1}^n. In particular, we establish the following results. 1. The problem of exactly computing the TV distance of two
Bhattacharyya, Arnab +5 more
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Dynamic Programming Subject to Total Variation Distance Ambiguity [PDF]
SIAM Journal on Control and Optimization, 2015 26 pages, 2 figures, To be submitted on Siam Journal on Control and ...
Tzortzis, I. +5 more
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Total Variation Distance Meets Probabilistic Inference
, 2023 In this paper, we establish a novel connection between total variation (TV) distance estimation and probabilistic inference. In particular, we present an efficient, structure-preserving reduction from relative approximation of TV distance to probabilistic inference over directed graphical models.
Bhattacharyya, Arnab +5 more
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Extremum Problems With Total Variation Distance and Their Applications [PDF]
IEEE Transactions on Automatic Control, 2014 The aim of this paper is to investigate extremum problems with pay-off being the total variational distance metric defined on the space of probability measures, subject to linear functional constraints on the space of probability measures, and vice-versa; that is, with the roles of total variational metric and linear functional interchanged.
Charalambous, Charalambos D. +7 more
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Distributionally Robust Model Predictive Control With Total Variation Distance
IEEE Control Systems Letters, 2022 This paper studies the problem of distributionally robust model predictive control (MPC) using total variation distance ambiguity sets. For a discrete-time linear system with additive disturbances, we provide a conditional value-at-risk reformulation of the MPC optimization problem that is distributionally robust in the expected cost and chance ...
Anushri Dixit +2 more
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On the total variation distance of labelled Markov chains [PDF]
Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 2014 Labelled Markov chains (LMCs) are widely used in probabilistic verification, speech recognition, computational biology, and many other fields. Checking two LMCs for equivalence is a classical problem subject to extensive studies, while the total variation distance provides a natural measure for the "inequivalence" of two LMCs: it is the maximum ...
Chen, Taolue, Kiefer, Stefan
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Total Variation Distance for Poisson Subset Numbers
Annals of Combinatorics, 2006 Let n be an integer and A0,..., A k random subsets of {1,..., n} of fixed sizes a0,..., a k , respectively chosen independently and uniformly. We provide an explicit and easily computable total variation bound between the distance from the random variable
Goldstein, L, Reinert, G
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Channel discord and distortion
New Journal of Physics, 2021 Discord, originally notable as a signature of bipartite quantum correlation, in fact can be nonzero classically, i.e. arising from noisy measurements by one of the two parties.
Wei-Wei Zhang +2 more
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Sparse Covers for Sums of Indicators [PDF]
, 2014 For all $n, \epsilon >0$, we show that the set of Poisson Binomial distributions on $n$ variables admits a proper $\epsilon$-cover in total variation distance of size $n^2+n \cdot (1/\epsilon)^{O(\log^2 (1/\epsilon))}$, which can also be computed in ...
Daskalakis, Constantinos +1 more
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