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Negative dependence of sequences of random variables is often an interesting characteristic of their distribution, as well as a useful tool for studying various asymptotic results, including central limit theorems, Poisson approximations,…

Probability · Mathematics 2022-08-26 Yaakov Malinovsky , Yosef Rinott

Random variables equidistributed on convex bodies have received quite a lot of attention in the last few years. In this paper we prove the negative association property (which generalizes the subindependence of coordinate slabs) for…

Probability · Mathematics 2008-03-05 Marcin Pilipczuk , Jakub Onufry Wojtaszczyk

We present an in-depth study of the problem of multiple-shot discrimination of von Neumann measurements in finite-dimensional Hilbert spaces. Specifically, we consider two scenarios: minimum error and unambiguous discrimination. In the case…

A common challenge in estimating parameters of probability density functions is the intractability of the normalizing constant. While in such cases maximum likelihood estimation may be implemented using numerical integration, the approach…

Machine Learning · Statistics 2019-05-21 Shiqing Yu , Mathias Drton , Ali Shojaie

This paper presents a new approach to conditional inference, based on the simulation of samples conditioned by a statistics of the data. Also an explicit expression for the approximation of the conditional likelihood of long runs of the…

Applications · Statistics 2012-02-07 Michel Broniatowski , Virgile Caron

The argument of environment-assisted invariance (known as envariance) implying Born's rule is widely used in models for quantum measurement to reason that they must yield the correct statistics, specifically for linear models. However, it…

Quantum Physics · Physics 2023-03-22 Lotte Mertens , Jasper van Wezel

In the present paper, we consider the two-color nonlinear unbalanced urn model, under a drawing rule reinforced by an $\mathbb{R}^+$-valued concave function and an unbalanced replacement matrix. The large deviation inequalities for the…

Probability · Mathematics 2024-09-13 Jianan Shi , Zhenhong Yu , Yu Miao

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

We consider an empirical likelihood framework for inference for a statistical model based on an informative sampling design. Covariate information is incorporated both through the weights and the estimating equations. The estimator is based…

Methodology · Statistics 2019-05-03 Sanjay Chaudhuri , Mark S. Handcock

It has become increasingly common nowadays to collect observations of feature and response pairs from different environments. As a consequence, one has to apply learned predictors to data with a different distribution due to distribution…

Methodology · Statistics 2023-10-31 Kang Du , Yu Xiang

Almost all Bell-inequality experiments to date have used postselection, and therefore relied on the fair sampling assumption for their interpretation. The standard form of the fair sampling assumption is that the loss is independent of the…

Quantum Physics · Physics 2010-01-29 Dominic W. Berry , Hyunseok Jeong , Magdalena Stobinska , Timothy C. Ralph

The paper is concerned with inference for a parameter of interest in models that share a common interpretation for that parameter but that may differ appreciably in other respects. We study the general structure of models under which the…

Statistics Theory · Mathematics 2024-08-06 Heather Battey , Nancy Reid

Predictive mean matching (PMM) is a popular imputation strategy that imputes missing values by borrowing observed values from other cases with similar expectations. We show that, unlike other imputation strategies, PMM is not guaranteed to…

Methodology · Statistics 2025-07-01 Paul T. von Hippel

We systematically study antithetic initial noise in diffusion models, discovering that pairing each noise sample with its negation consistently produces strong negative correlation. This universal phenomenon holds across datasets, model…

Machine Learning · Computer Science 2026-02-02 Jing Jia , Sifan Liu , Bowen Song , Wei Yuan , Liyue Shen , Guanyang Wang

A deterministic sequence of real numbers in the unit interval is called \emph{equidistributed} if its empirical distribution converges to the uniform distribution. Furthermore, the limit distribution of the pair correlation statistics of a…

Number Theory · Mathematics 2016-12-19 Christoph Aistleitner , Thomas Lachmann , Florian Pausinger

We consider voting rules in settings where voters' identities are difficult to verify. Voters can manipulate the process by casting multiple votes under different identities or abstaining from voting. Immunities to such manipulations are…

Theoretical Economics · Economics 2026-05-15 Agustin G. Bonifacio , Federico Fioravanti

The symmetric random walk is known to be recurrent in one and two dimensions, and becomes transient in three or higher dimensions. We compare the symmetric random walk to walks driven by certain \polya\ urns. We show that, in contrast, if…

Probability · Mathematics 2026-04-22 Srinivasan Balaji , Hosam Mahmoud

We study the symmetry and integrability of a modified Camassa-Holm Equation (MCH), with an arbitrary parameter $k,$ of the form $$u_{t}+k(u-u_{xx})^2u_{x}-u_{xxt}+(u^{2}-{u_{x}}^2)(u_{x}-u_{xxx})=0.$$ By using Lie point symmetries we reduce…

Exactly Solvable and Integrable Systems · Physics 2019-11-14 A Durga Devi , K Krishnakumar , R Sinuvasan , PGL Leach

We show that a QWEP von Neumann algebra has the weak* positive approximation property if and only if it is seemingly injective in the following sense: there is a factorization of the identity of $M$ $$Id_M=vu: M{\buildrel…

Operator Algebras · Mathematics 2023-04-05 Gilles Pisier

We consider the problem of whether a given decision model, working with structured data, has individual fairness. Following the work of Dwork, a model is individually biased (or unfair) if there is a pair of valid inputs which are close to…

Machine Learning · Computer Science 2020-06-23 Philips George John , Deepak Vijaykeerthy , Diptikalyan Saha