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Not only are the foundation theories mutually compatible, they are also compatible with local realism once this concept is properly formulated (without presuming atomism in addition to locality). Relativity Theory is reconstructed in the…

Quantum Physics · Physics 2007-05-23 A. Laidlaw

We consider the problem of closeness testing for two discrete distributions in the practically relevant setting of \emph{unequal} sized samples drawn from each of them. Specifically, given a target error parameter $\varepsilon > 0$, $m_1$…

Machine Learning · Computer Science 2015-04-20 Bhaswar B. Bhattacharya , Gregory Valiant

A locally testable code is an error-correcting code that admits very efficient probabilistic tests of membership. Tensor codes provide a simple family of combinatorial constructions of locally testable codes that generalize the family of…

Quantum Physics · Physics 2022-12-07 Zhengfeng Ji , Anand Natarajan , Thomas Vidick , John Wright , Henry Yuen

In Bayesian analysis, the posterior follows from the data and a choice of a prior and a likelihood. One hopes that the posterior is robust to reasonable variation in the choice of prior, since this choice is made by the modeler and is often…

Methodology · Statistics 2016-12-07 Ryan Giordano , Tamara Broderick , Michael Jordan

We extend the recent bounds of Sason and Verd\'u relating R\'enyi entropy and Bayesian hypothesis testing [arXiv:1701.01974] to the quantum domain and show that they have a number of different applications. First, we obtain a sharper bound…

Quantum Physics · Physics 2017-10-25 Joseph M. Renes

Many standard estimators such as several maximum likelihood estimators or the empirical estimator for any law-invariant convex risk measure are not (qualitatively) robust in the classical sense. However, these estimators may nevertheless…

Statistics Theory · Mathematics 2016-06-21 Volker Krätschmer , Alexander Schied , Henryk Zähle

We study a local thinning $T_r$ that retains a point with probability $p(n_r)$, where $n_r$ counts neighbors within radius $r$. For Poisson input with spatially varying intensity, we obtain an exact intensity via a Poisson--mixture formula…

Probability · Mathematics 2025-11-14 Kateryna Hlyniana

We consider the distributed detection problem of a temporally correlated random radio source signal using a wireless sensor network capable of measuring the energy of the received signals. It is well-known that optimal tests in the…

Signal Processing · Electrical Eng. & Systems 2023-12-20 Juan Augusto Maya , Leonardo Rey Vega , Andrea M. Tonello

Clauser-Horne-Shimony-Holt inequality can give values between the classical bound, 2, and Tsirelson's bound, 2 \sqrt 2. However, for a given set of local observables, there are values in this range which no quantum state can attain. We…

Quantum Physics · Physics 2009-07-28 Adan Cabello

In the device-independent quantum information approach, the implementation of a given task can be self-tested solely from the recorded statistics and without detailed models for the employed devices. Even though experimentally demanding, it…

Quantum Physics · Physics 2021-01-20 Máté Farkas , Nayda Guerrero , Jaime Cariñe , Gustavo Cañas , Gustavo Lima

Plausibility is a formalization of exact tests for parametric models and generalizes procedures such as Fisher's exact test. The resulting tests are based on cumulative probabilities of the probability density function and evaluate…

Statistics Theory · Mathematics 2021-09-13 Stefan Böhringer , Dietmar Lohmann

Replicability and reproducibility of experimental results are primary concerns in all the areas of science and IR is not an exception. Besides the problem of moving the field towards more reproducible experimental practices and protocols,…

Information Retrieval · Computer Science 2020-10-27 Timo Breuer , Nicola Ferro , Norbert Fuhr , Maria Maistro , Tetsuya Sakai , Philipp Schaer , Ian Soboroff

A number of approaches have dealt with statistical assessment of self-similarity, and many of those are based on multiscale concepts. Most rely on certain distributional assumptions which are usually violated by real data traces, often…

Methodology · Statistics 2022-01-25 Erin K. Hamilton , Seonghye Jeon , Pepa Ramirez Cobo , Kichun Sky Lee , Brani Vidakovic

Optimal experimental design provides a way of determining a-priori the best locations at which to place accelerometers in vibrations analysis experiments. However, in practice, sensors often fail during experimentation due high mechanical…

Computational Engineering, Finance, and Science · Computer Science 2026-04-17 Rebekah White , Chandler Smith , Drew Kouri , Jace Ritchie , Wilkins Aquino , Timothy Walsh

I formulate the problem of closing the detection loophole as a constrained optimization problem. Numerical methods can then be used to maximize the detector efficiency subject to the constraint that there exists a local realist explanation…

Quantum Physics · Physics 2008-05-06 James H. Bigelow

This paper proposes a new test for a change point in the mean of high-dimensional data based on the spatial sign and self-normalization. The test is easy to implement with no tuning parameters, robust to heavy-tailedness and theoretically…

Methodology · Statistics 2022-06-07 Feiyu Jiang , Runmin Wang , Xiaofeng Shao

We construct and analyze an estimator of association between random variables based on their similarity in both direction and magnitude. Under special conditions, the proposed measure becomes a robust and consistent estimator of the linear…

Econometrics · Economics 2026-01-21 Ilya Archakov

Self-testing was originally introduced as a device-independent method of certification of entangled quantum states and local measurements performed on them. Recently, in [F. Baccari \textit{et al.}, arXiv:2003.02285] the notion of state…

Quantum Physics · Physics 2021-07-02 Owidiusz Makuta , Remigiusz Augusiak

Detection of rare traits or diseases in a large population is challenging. Pool testing allows covering larger swathes of population at a reduced cost, while simplifying logistics. However, testing precision decreases as it becomes unclear…

Information Theory · Computer Science 2021-06-22 Éric Brier , Megi Dervishi , Rémi Géraud-Stewart , David Naccache , Ofer Yifrach-Stav

Probably Approximately Correct (PAC) bounds are widely used to derive probabilistic guarantees for the generalisation of machine learning models. They highlight the components of the model which contribute to its generalisation capacity.…

Machine Learning · Computer Science 2024-07-30 Thomas Walker , Alessio Lomuscio