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The Wasserstein distance provides a notion of dissimilarities between probability measures, which has recent applications in learning of structured data with varying size such as images and text documents. In this work, we study the…

Machine Learning · Statistics 2022-06-28 Donlapark Ponnoprat

General sufficient conditions are given for absolute continuity and convergence in variation of the distributions of the unctionals on a probability space, generated by a Poisson point measure. The phase space of the Poisson point measure…

Probability · Mathematics 2010-10-05 Alexey M. Kulik

Despite the popularity and practical success of total variation (TV) regularization for function estimation, surprisingly little is known about its theoretical performance in a statistical setting. While TV regularization has been known for…

Statistics Theory · Mathematics 2026-05-08 Miguel del Álamo , Housen Li , Axel Munk

We consider the invariant measure of homogeneous random walks in the quarter-plane. In particular, we consider measures that can be expressed as a finite linear combination of geometric terms and present conditions on the structure of these…

Probability · Mathematics 2014-07-02 Yanting Chen , Richard J. Boucherie , Jasper Goseling

We are interested in the estimation of the distance in total variation $$ \Delta := \|P_{f(X)} - P_{g(X)}\|_{\mathrm var} $$ between distributions of random variables $f(X)$ and $g(X)$ in terms of proximity of $f$ and $g.$ We propose a…

Probability · Mathematics 2017-06-21 Youri Davydov

Total Variation (TV) is a popular regularization strategy that promotes piece-wise constant signals by constraining the $\ell_1$-norm of the first order derivative of the estimated signal. The resulting optimization problem is usually…

Optimization and Control · Mathematics 2020-10-20 Hamza Cherkaoui , Jeremias Sulam , Thomas Moreau

We propose a second-order total generalized variation (TGV) regularization for the reconstruction of the initial condition in variational data assimilation problems. After showing the equivalence between TGV regularization and the Bayesian…

Optimization and Control · Mathematics 2018-04-13 J. C. De los Reyes , E. Loayza

Data represented by probability measures arise as empirical distributions, posterior distributions, and feature-based representations of complex objects. We study heterogeneity in a population of probability measures through the expected…

Methodology · Statistics 2026-03-17 Kisung You

Let $(T,d)$ be a metric space and $\phi:\mathbb{R}_+\to \mathbb{R}$ an increasing, convex function with $\phi(0)=0$. We prove that if $m$ is a probability measure $m$ on $T$ which is majorizing with respect to $d,\phi$, that is,…

Probability · Mathematics 2007-05-23 Witold Bednorz

We introduce distance measures between quantum states, measurements, and channels based on their statistical distinguishability in generic experiments. Specifically, we analyze the average Total Variation Distance (TVD) between output…

Quantum Physics · Physics 2023-09-13 Filip B. Maciejewski , Zbigniew Puchała , Michał Oszmaniec

Quantum coherence, as a direct manifestation of the quantum superposition principle, is a crucial resource in quantum information processing. Block coherence resource theory generalizes the traditional coherence framework by defining…

Quantum Physics · Physics 2026-03-31 Xiangyu Chen , Qiang Lei

This work aims to explore the regularity properties of the smoothed-TV regularization for the functions is of the class H\"older continuous. Over some compact and convex domain $\Omega,$ we study construction of multivariate function…

Optimization and Control · Mathematics 2015-09-08 Erdem Altuntac

Everettian Quantum Mechanics, or the Many Worlds Interpretation, lacks an explanation for quantum probabilities. We show that the values given by the Born rule equal projection factors, describing the contraction of Lebesgue measures in…

Quantum Physics · Physics 2020-07-24 André L. G. Mandolesi

The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty function motivated by the recent progress in the statistical…

Computer Vision and Pattern Recognition · Computer Science 2011-07-28 Aditya Chopra , Heng Lian

In this paper, we consider a backward problem for a time-space fractional diffusion process. For this problem, we propose to construct the initial data by minimizing data residual error in fourier space domain and variable total variation…

Numerical Analysis · Mathematics 2016-05-24 Junxiong Jia , Jigen Peng , Jinghuai Gao , Yujiao Li

We propose a novel approach to quantify quantum coherence which, contrary to the previous ones, does not rely on resource theory but rather on ontological considerations. In this framework, coherence is understood as the ability for a…

Mathematical Physics · Physics 2025-02-17 Antoine Soulas

A combinatorial proof of the Gaussian product inequality (GPI) is given under the assumption that each component of a centered Gaussian random vector $\boldsymbol{X} = (X_1, \ldots, X_d)$ of arbitrary length can be written as a linear…

Probability · Mathematics 2022-11-18 Christian Genest , Frédéric Ouimet

We investigate general probabilistic theories in which every mixed state has a purification, unique up to reversible channels on the purifying system. We show that the purification principle is equivalent to the existence of a reversible…

Quantum Physics · Physics 2010-07-02 G. Chiribella , G. M. D'Ariano , P. Perinotti

We study generic holomorphic families of dynamical systems presenting problems of small divisors with fixed arithmetic. We prove that we have convergence for all parameter values or divergence everywhere except for an exceptional set in the…

Dynamical Systems · Mathematics 2009-10-31 Ricardo Perez-Marco

We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qualitative properties (in particular a form of maximum principle and in some cases, a minimum principle as well). Finally, we establish a…

Analysis of PDEs · Mathematics 2018-07-09 Guillaume Carlier , Clarice Poon