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We propose an uncertainty-complementarity balance relation and build quantitative connections among non-locality, complementarity, and uncertainty. Our balance relation, which is formulated in a theory-independent manner, states that for…

Quantum Physics · Physics 2018-08-21 Liang-Liang Sun , Sixia Yu , Zeng-Bing Chen

The sharp constants in a family of exponential Sobolev type inequalities in Gauss space are exhibited. They constitute the Gaussian analogues of the Moser inequality in the borderline case of the Sobolev embedding in the Euclidean space.…

Functional Analysis · Mathematics 2020-10-09 Andrea Cianchi , Vít Musil , Luboš Pick

Real-world object classes appear in imbalanced ratios. This poses a significant challenge for classifiers which get biased towards frequent classes. We hypothesize that improving the generalization capability of a classifier should improve…

Computer Vision and Pattern Recognition · Computer Science 2019-01-24 Munawar Hayat , Salman Khan , Waqas Zamir , Jianbing Shen , Ling Shao

All correlation measures, classical and quantum, must be monotonic under local operations. In this paper, we characterize monotonic formulas that are linear combinations of the von Neumann entropies associated with the quantum state of a…

Quantum Physics · Physics 2020-09-29 Mohammad A. Alhejji , Graeme Smith

The high efficiency of a recently proposed method for computing with Gaussian processes relies on expanding a (translationally invariant) covariance kernel into complex exponentials, with frequencies lying on a Cartesian equispaced grid.…

Numerical Analysis · Mathematics 2023-05-19 Alex Barnett , Philip Greengard , Manas Rachh

Let $N$ be a finite set, let $p \in (0,1)$, and let $N_p$ denote a random binomial subset of $N$ where every element of $N$ is taken to belong to the subset independently with probability $p$ . This defines a product measure $\mu_p$ on the…

Combinatorics · Mathematics 2014-09-25 Ehud Friedgut , Jeff Kahn , Clara Shikhelman

We improve both upper and lower bounds for the distribution-free testing of monotone conjunctions. Given oracle access to an unknown Boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$ and sampling oracle access to an unknown distribution…

Discrete Mathematics · Computer Science 2015-11-12 Xi Chen , Jinyu Xie

We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain…

Machine Learning · Computer Science 2024-06-18 Stefano Favaro , Boris Hanin , Domenico Marinucci , Ivan Nourdin , Giovanni Peccati

In this paper a reduction and equivalence theorems for the boundedness of the composition of a quasilinear operator $T$ with the Hardy and Copson operators in weighted Lebesgue spaces are proved. New equivalence theorems are obtained for…

Classical Analysis and ODEs · Mathematics 2015-03-16 Amiran Gogatishvili , Rza Mustafayev

We provide a new construction for a set of boxes approximating axis-parallel boxes of fixed volume in $[0, 1]^d$. This improves upper bounds for the minimal dispersion of a point set in the unit cube and its inverse in both the periodic and…

Metric Geometry · Mathematics 2022-01-24 Alexander E. Litvak , Galyna V. Livshyts

It is shown that random quantum spin systems with centered disorder satisfy correlation inequalities previously proved (arXiv:cond-mat/0612371) in the classical case. Consequences include monotone approach of pressure and ground state…

Statistical Mechanics · Physics 2015-05-13 Pierluigi Contucci , Joel L. Lebowitz

We consider the problem of joint estimation of structured covariance matrices. Assuming the structure is unknown, estimation is achieved using heterogeneous training sets. Namely, given groups of measurements coming from centered…

Statistics Theory · Mathematics 2016-04-20 Ilya Soloveychik , Ami Wiesel

Inspired by Milman's recent observation, we prove that the Gaussian correlation inequality holds for convex sets having the same barycenter, and especially for centered ones. This gives an affirmative answer to the problem proposed by…

Functional Analysis · Mathematics 2025-11-13 Shohei Nakamura , Hiroshi Tsuji

It is well known that central order statistics exhibit a central limit behavior and converge to a Gaussian distribution as the sample size grows. This paper strengthens this known result by establishing an entropic version of the CLT that…

Information Theory · Computer Science 2022-05-11 Martina Cardone , Alex Dytso , Cynthia Rush

A general theory is provided delivering convergence of maximal cyclically monotone mappings containing the supports of coupling measures of sequences of pairs of possibly random probability measures on Euclidean space. The theory is based…

Statistics Theory · Mathematics 2022-08-05 Johan Segers

Correlation self-testing of quantum theory involves identifying a task or set of tasks whose optimal performance can be achieved only by theories that can realise the same set of correlations as quantum theory in every causal structure.…

Quantum Physics · Physics 2025-11-06 Kuntal Sengupta , Mirjam Weilenmann , Roger Colbeck

We show that any sequence $(x_n)_{n \in \mathbb{N}} \subseteq [0,1]$ that has Poissonian correlations of $k$-th order is uniformly distributed, also providing a quantitative description of this phenomenon. Additionally, we extend…

Number Theory · Mathematics 2022-09-26 Manuel Hauke , Agamemnon Zafeiropoulos

Quantitative limit theorems for non-linear functionals on the Wiener space are considered. Given the possibly infinite sequence of kernels of the chaos decomposition of such a functional, an estimate for different probability distances…

Probability · Mathematics 2016-10-06 Tobias Fissler , Christoph Thaele

Distance covariance and distance correlation are scalar coefficients that characterize independence of random vectors in arbitrary dimension. Properties, extensions, and applications of distance correlation have been discussed in the recent…

Methodology · Statistics 2014-07-10 Gabor J. Szekely , Maria L. Rizzo

We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existing relaxed triangle inequalities for KL divergence critically rely on the assumption that…

Machine Learning · Computer Science 2026-04-17 Jialu Pan , Yufeng Zhang , Nan Hu , Zhenbang Chen , Ji Wang , Keqin Li