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Covariate shift arises when covariate distributions differ between source and target populations while the conditional distribution of the response remains invariant, and it underlies problems in missing data and causal inference. We…

Methodology · Statistics 2026-01-13 Junjun Lang , Qiong Zhang , Yukun Liu

We give new combinatorial proofs of known almost-periodicity results for sumsets of sets with small doubling in the spirit of Croot and Sisask, whose almost-periodicity lemma has had far-reaching implications in additive combinatorics. We…

Discrete Mathematics · Computer Science 2019-06-14 Eli Ben-Sasson , Noga Ron-Zewi , Madhur Tulsiani , Julia Wolf

The Assouad and quasi-Assouad dimensions of a metric space provide information about the extreme local geometric nature of the set. The Assouad dimension of a set has a measure theoretic analogue, which is also known as the upper regularity…

Metric Geometry · Mathematics 2018-11-15 Kathryn Hare , Kevin Hare , Sascha Troscheit

A new class of distances appropriate for measuring similarity relations between sequences, say one type of similarity per distance, is studied. We propose a new ``normalized information distance'', based on the noncomputable notion of…

Computational Complexity · Computer Science 2011-11-09 Ming Li , Xin Chen , Xin Li , Bin Ma , Paul Vitanyi

In [arXiv 0811.3913] the authors introduced the notion of quasi-polynomial function as being a mapping f: X^n -> X defined and valued on a bounded chain X and which can be factorized as f(x_1,...,x_n)=p(phi(x_1),...,phi(x_n)), where p is a…

Functional Analysis · Mathematics 2010-11-23 Miguel Couceiro , Jean-Luc Marichal

A pseudo-polynomial time $(1 + \varepsilon)$-approximation algorithm is presented for computing the integral and average Fr\'{e}chet distance between two given polygonal curves $T_1$ and $T_2$. In particular, the running time is…

Computational Geometry · Computer Science 2015-12-11 Anil Maheshwari , Jörg-Rüdiger Sack , Christian Scheffer

We establish explicit bounds on the convex distance between the distribution of a vector of smooth functionals of a Gaussian field, and that of a normal vector with a positive definite covariance matrix. Our bounds are commensurate to the…

Probability · Mathematics 2021-02-26 Ivan Nourdin , Giovanni Peccati , Xiaochuan Yang

Parametric Presburger arithmetic concerns families of sets S_t in Z^d, for t in N, that are defined using addition, inequalities, constants in Z, Boolean operations, multiplication by t, and quantifiers on variables ranging over Z. That is,…

Combinatorics · Mathematics 2017-01-18 Tristram Bogart , John Goodrick , Kevin Woods

We establish a set of relations between several quite diverse types of weighted inequalities involving various integral operators and fairly general quasinorm-like functionals which we call sub-monotone. The main result enables one to solve…

Classical Analysis and ODEs · Mathematics 2025-03-13 Amiran Gogatishvili , Luboš Pick

The Quasi Manhattan Wasserstein Distance (QMWD) is a metric designed to quantify the dissimilarity between two matrices by combining elements of the Wasserstein Distance with specific transformations. It offers improved time and space…

Machine Learning · Computer Science 2023-10-20 Evan Unit Lim

In 1991 J.F. Aarnes introduced the concept of quasi-measures in a compact topological space $\Omega$ and established the connection between quasi-states on $C (\Omega)$ and quasi-measures in $\Omega$. This work solved the linearity problem…

Statistics Theory · Mathematics 2017-06-22 Gunnar Taraldsen

In this work it is shown that certain interesting types of quasi-orthogonal system of subalgebras (whose existence cannot be ruled out by the trivial necessary conditions) cannot exist. In particular, it is proved that there is no…

Mathematical Physics · Physics 2010-02-02 Mihály Weiner

The purpose of this work is to investigate root finding problems defined on (quasi-)metric spaces, and ranging in Euclidean spaces. The motivation for this line of inquiry stems from recent models in biology and phylogenetics, where…

Optimization and Control · Mathematics 2025-10-28 Titus Pinta

For a family of continuous functions $f_1,f_2,\dots \colon I \to \mathbb{R}$ ($I$ is a fixed interval) with $f_1\le f_2\le \dots$ define a set $$ I_f:=\big\{x \in I \colon \lim_{n \to \infty} f_n(x)=+\infty\big\}.$$ We study the properties…

Classical Analysis and ODEs · Mathematics 2024-03-29 Karol Gryszka , Paweł Pasteczka

Wasserstein distances define a metric between probability measures on arbitrary metric spaces, including meta-measures (measures over measures). The resulting Wasserstein over Wasserstein (WoW) distance is a powerful, but computationally…

Machine Learning · Computer Science 2026-02-20 Moritz Piening , Robert Beinert

The Gromov-Wasserstein (GW) distance has gained increasing interest in the machine learning community in recent years, as it allows for the comparison of measures in different metric spaces. To overcome the limitations imposed by the equal…

Machine Learning · Computer Science 2025-03-28 Yikun Bai , Rocio Diaz Martin , Abihith Kothapalli , Hengrong Du , Xinran Liu , Soheil Kolouri

Let $S_m f$ denote the $m$-th partial sum of the Walsh-Fourier series of $f \in L^1$. For an increasing sequence $a=(a(n))_{n \geq 1}$ of positive integers, consider the arithmetic means $$ \sigma_N f:=\frac{1}{N} \sum_{n=1}^N S_{a(n)} f .…

Classical Analysis and ODEs · Mathematics 2026-05-07 Ushangi Goginava

We derive an expression that allows for the unambiguous evaluation of the overlap between two arbitrary quasiparticle vacua, including its sign. Our expression is based on the Pfaffian of a skew-symmetric matrix, extending the formula…

Nuclear Theory · Physics 2013-10-22 Benoît Avez , Michael Bender

We introduce the notions of in-betweenness and monotonicity with respect to a metric, for operator means. These notions can be seen as generalising their natural counterpart for scalar means, and as a relaxation of the notion of geodesity.…

Functional Analysis · Mathematics 2013-04-23 Koenraad M. R. Audenaert

Majorization theory is a powerful mathematical tool to compare the disorder in distributions, with wide-ranging applications in many fields including mathematics, physics, information theory, and economics. While majorization theory…