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Let $(X, \mathscr{L}, \lambda)$ and $(Y, \mathscr{M}, \mu)$ be finite measure spaces for which there exist $A \in \mathscr{L}$ and $B \in \mathscr{M}$ with either $0 < \lambda(A) < 1 < \lambda(X)$ and $0 < \mu(B) < \mu(Y)$, or the other way…

Functional Analysis · Mathematics 2023-05-08 Dorota Glazowska , Paolo Leonetti , Janusz Matkowski , Salvatore Tringali

In this article, we establish weighted strong and weak type inequalities for non-commutative square functions that naturally arise in the analysis of differences between ball averages and martingale sequences within the framework of group…

Functional Analysis · Mathematics 2026-01-05 Panchugopal Bikram , Diptesh Saha

The paper deals with the problem of existence of a convergent "strong" normal form in the neighbourhood of an equilibrium, for a finite dimensional system of differential equations with analytic and time-dependent non-linear term. The…

Dynamical Systems · Mathematics 2016-09-27 Alessandro Fortunati , Stephen Wiggins

A carefully written Nirenberg's proof of the well known Gagliardo-Nirenberg interpolation inequality for intermediate derivatives in $\mathbb{R}^n$ seems, surprisingly, to be missing in literature. In our paper we shall first introduce this…

Functional Analysis · Mathematics 2018-12-12 Alberto Fiorenza , Maria Rosaria Formica , Tomáš Roskovec , Filip Soudský

We revisit extending the Kolmogorov-Smirnov distance between probability distributions to the multidimensional setting and make new arguments about the proper way to approach this generalization. Our proposed formulation maximizes the…

Computation · Statistics 2025-04-16 Peter Matthew Jacobs , Foad Namjoo , Jeff M. Phillips

Chernoff bounds are a powerful application of the Markov inequality to produce strong bounds on the tails of probability distributions. They are often used to bound the tail probabilities of sums of Poisson trials, or in regression to…

Statistics Theory · Mathematics 2022-05-24 D. K. L. Shiu

We propose the use of entangled pairs of neutral kaons, considered as a promising tool to close the well known loopholes affecting generic Bell's inequality tests, in a specific Hardy-type experiment. Hardy's contradiction without…

Quantum Physics · Physics 2009-11-07 A. Bramon , G. Garbarino

We study the Cauchy problem involving non-local Ornstein-Uhlenbeck operators in finite and infinite dimensions. We prove classical solvability without requiring that the L\'evy measure corresponding to the large jumps part has a first…

Analysis of PDEs · Mathematics 2024-05-07 Enrico Priola , Stefano Tracà

A non-parametric k-nearest neighbour based entropy estimator is proposed. It improves on the classical Kozachenko-Leonenko estimator by considering non-uniform probability densities in the region of k-nearest neighbours around each sample…

Information Theory · Computer Science 2016-01-27 Damiano Lombardi , Sanjay Pant

We consider the problem of unambiguous (error-free) discrimination of N linearly independent pure quantum states with prior probabilities, where the goal is to find a measurement that maximizes the average probability of success. We derive…

Quantum Physics · Physics 2015-06-19 Somshubhro Bandyopadhyay

The log-rank test is most powerful under proportional hazards (PH). In practice, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods are needed to restore the efficiency of…

In this paper, we obtain Cordes-Nirenberg type estimates for nonlocal parabolic equations on the more flexible solution space $L^{\iy}_T(L^1_{\om})$ than the classical solution space $\rB(\BR^n_T)$ consisting of all bounded functions on…

Classical Analysis and ODEs · Mathematics 2015-08-18 Yong-Cheol Kim , Ki-Ahm Lee

We examine a family of intrinsic performance measures in terms of probability distributions that generalize Hellinger distance and Fisher information. They are applied to quantum metrology to assess the uncertainty in the detection of…

Quantum Physics · Physics 2015-03-20 Alfredo Luis , Alfonso Rodil

An extension of the Gauss-Newton algorithm is proposed to find local minimizers of penalized nonlinear least squares problems, under generalized Lipschitz assumptions. Convergence results of local type are obtained, as well as an estimate…

Optimization and Control · Mathematics 2011-03-03 Saverio Salzo , Silvia Villa

Marginal structural models are a popular method for estimating causal effects in the presence of time-varying exposures. In spite of their popularity, no scalable non-parametric estimator exist for marginal structural models with…

Methodology · Statistics 2024-09-30 Axel Martin , Michele Santacatterina , Iván Díaz

We propose a new nonparametric test for the supposition of independence between two continuous random variables. The test is based on the size of the longest increasing subsequence of a random permutation. We identified the independence…

Methodology · Statistics 2015-03-13 Jesus E. Garcia , Veronica A. Gonzalez-Lopez

In this article, we construct semiparametrically efficient estimators of linear functionals of a probability measure in the presence of side information using an easy empirical likelihood approach. We use estimated constraint functions and…

Methodology · Statistics 2023-03-01 Shan Wang , Hanxiang Peng

We prove strong laws of large numbers under intermediate trimming for Birkhoff sums over subshifts of finite type. This gives another application of a previous trimming result only proven for interval maps. In case of Markov measures we…

Dynamical Systems · Mathematics 2021-11-25 Marc Kesseböhmer , Tanja Schindler

In the context of Hardy inequalities for the fractional Laplacian $(-\Delta_{\mathbb{N}})^{\sigma}$ on the discrete half-line $\mathbb{N}$, we provide an optimal Hardy-weight $W^{\mathrm{op}}_{\sigma}$ for exponents…

Analysis of PDEs · Mathematics 2025-07-10 Ujjal Das , Rubén de la Fuente-Fernández

A new computationally efficient dependence measure, and an adaptive statistical test of independence, are proposed. The dependence measure is the difference between analytic embeddings of the joint distribution and the product of the…

Machine Learning · Statistics 2016-10-18 Wittawat Jitkrittum , Zoltan Szabo , Arthur Gretton