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We argue that the conclusion about the invalidity of the Dirac conjecture, made in the paper by Wang, Li, and Wang (Int. J. Theor. Phys. 48 1894, 2009), was based upon a flawed analysis of the proposed counterexamples. In the case of the…

High Energy Physics - Theory · Physics 2011-12-30 N. Kiriushcheva , P. G. Komorowski , S. V. Kuzmin

Steve Gull, in unpublished work available on his Cambridge University homepage, has outlined a proof of Bell's theorem using Fourier theory. Gull's philosophy is that Bell's theorem (or perhaps a key lemma in its proof) can be seen as a…

Quantum Physics · Physics 2022-05-30 Richard D. Gill

Adaptivity is an important feature of data analysis---the choice of questions to ask about a dataset often depends on previous interactions with the same dataset. However, statistical validity is typically studied in a nonadaptive model,…

Machine Learning · Computer Science 2015-11-10 Raef Bassily , Kobbi Nissim , Adam Smith , Thomas Steinke , Uri Stemmer , Jonathan Ullman

This is one of the two papers where the optimized perturbation theory was first formulated. The other paper is published in Theor. Math. Phys. 28, 652--660 (1976). The main idea of the theory is to reorganize the perturbative sequence by…

Statistical Mechanics · Physics 2019-01-29 V. I. Yukalov

Generalized estimating equations (GEE) are widely used to analyze longitudinal data; however, they are not appropriate for heteroscedastic data, because they only estimate regressor effects on the mean response{\textemdash}and therefore do…

Methodology · Statistics 2020-12-29 Amadou Barry , Karim Oualkacha , Arthur Charpentier

Counterfactual explanations can be obtained by identifying the smallest change made to a feature vector to qualitatively influence a prediction; for example, from 'loan rejected' to 'awarded' or from 'high risk of cardiovascular disease' to…

Machine Learning · Computer Science 2020-05-05 Martin Pawelczyk , Johannes Haug , Klaus Broelemann , Gjergji Kasneci

Popular deterministic approximations of posterior distributions from, e.g. the Laplace method, variational Bayes and expectation-propagation, generally rely on symmetric approximating families, often taken to be Gaussian. This choice…

Methodology · Statistics 2026-01-19 Francesco Pozza , Daniele Durante , Botond Szabo

We propose a new approach to vague convergence of measures based on the general theory of boundedness due to Hu (1966). The article explains how this connects and unifies several frequently used types of vague convergence from the…

Probability · Mathematics 2019-12-30 Bojan Basrak , Hrvoje Planinić

Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This…

Economics · Quantitative Finance 2016-10-07 Enrico G. De Giorgi , Ola Mahmoud

Under expected utility the local index of absolute risk aversion has played a central role in many applications. Besides, its link with the "global" concepts of the risk and probability premia has reinforced its attractiveness. This paper…

Mathematical Finance · Quantitative Finance 2015-12-29 Louis R. Eeckhoudt , Roger J. A. Laeven

We present a {\sl non--perturbative} method, called {\sl Parametric Perturbation Theory} (PPT), which is alternative to the ordinary perturbation theory. The method relies on a principle of simplicity for the observable solutions, which are…

Other Condensed Matter · Physics 2007-05-23 Paolo Amore

In the absence of historical data for use as forecasting inputs, decision makers often ask a panel of judges to predict the outcome of interest, leveraging the wisdom of the crowd (Surowiecki 2005). Even if the crowd is large and skilled,…

Applications · Statistics 2024-04-30 Joseph Rilling

We consider the performance of non-optimal hedging strategies in exponential L\'evy models. Given that both the payoff of the contingent claim and the hedging strategy admit suitable integral representations, we use the Laplace transform…

Computational Finance · Quantitative Finance 2011-05-18 Stephan Denkl , Martina Goy , Jan Kallsen , Johannes Muhle-Karbe , Arnd Pauwels

We propose indifference pricing to estimate the value of the weak information. Our framework allows for tractability, quantifying the amount of additional information, and permits the description of the smallness and the stability with…

Mathematical Finance · Quantitative Finance 2024-08-06 Fabrice Baudoin , Oleksii Mostovyi

The Bell theorem stands as an insuperable roadblock in the path to a very desired intuitive solution of the EPR paradox and, hence, it lies at the core of the current lack of a clear interpretation of the quantum formalism. The theorem…

Quantum Physics · Physics 2022-02-22 David H. Oaknin

The review presents general methods for treating complicated problems that cannot be solved exactly and whose solution encounters two major difficulties. First, there are no small parameters allowing for the safe use of perturbation theory…

High Energy Physics - Theory · Physics 2021-05-27 V. I. Yukalov

We consider the nonparametric regression estimation problem of recovering an unknown response function f on the basis of spatially inhomogeneous data when the design points follow a known compactly supported density g with a finite number…

Methodology · Statistics 2012-10-29 Anestis Antoniadis , Marianna Pensky , Theofanis Sapatinas

Yager[5] proposed a transformation for opposing(negating) the occurence of an event that is not certain using the idea that one can oppose the occurence of any uncertain event by allocating its probability among the other outcomes in the…

Probability · Mathematics 2024-04-01 Amit Srivastava

Sums of independent, bounded random variables concentrate around their expectation approximately as well a Gaussian of the same variance. Well known results of this form include the Bernstein, Hoeffding, and Chernoff inequalities and many…

Discrete Mathematics · Computer Science 2017-04-25 Thomas Steinke , Jonathan Ullman

We consider Bayesian inference in inverse regression problems where the objective is to infer about unobserved covariates from observed responses and covariates. We establish posterior consistency of such unobserved covariates in Bayesian…

Statistics Theory · Mathematics 2020-05-04 Debashis Chatterjee , Sourabh Bhattacharya