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In this paper, we consider the sublinear expectation on bounded random variables. With the notion of uncorrelatedness for random variables under the sublinear expectation, a weak law of large numbers is obtained. With the notion of…

Probability · Mathematics 2023-11-17 Wenhao Li , Chuanfeng Sun

A general Bayesian framework for model selection on random network models regarding their features is considered. The goal is to develop a principle Bayesian model selection approach to compare different fittable, not necessarily nested,…

Methodology · Statistics 2020-04-30 Papamichalis Marios

The hypothesis of randomness is fundamental in statistical machine learning and in many areas of nonparametric statistics; it says that the observations are assumed to be independent and coming from the same unknown probability…

Probability · Mathematics 2022-02-08 Vladimir Vovk

The celebrated minimax principle of Yao (1977) says that for any Boolean-valued function $f$ with finite domain, there is a distribution $\mu$ over the domain of $f$ such that computing $f$ to error $\epsilon$ against inputs from $\mu$ is…

Computational Complexity · Computer Science 2020-09-21 Shalev Ben-David , Eric Blais

Let $k$ be a field, $V$ a $k$-vector space and $X$ be a subset of $V $. A function $f:X\to k$ is weakly polynomial of degree $\leq a$, if the restriction of $f$ on any affine subspace $L\subset X$ is a polynomial of degree $\leq a$. In this…

Algebraic Geometry · Mathematics 2019-02-06 David Kazhdan , Tamar Ziegler

Power-law distributions are typical macroscopic features occurring in almost all complex systems observable in nature. As a result, researchers in quantitative analyses must often generate random synthetic variates obeying power-law…

Physics and Society · Physics 2014-11-11 Filippo Radicchi

The concept of open weak CAD is introduced. Every open CAD is an open weak CAD. On the contrary, an open weak CAD is not necessarily an open CAD. An algorithm for computing projection polynomials of open weak CADs is proposed. The key idea…

Symbolic Computation · Computer Science 2019-03-28 Jingjun Han , Liyun Dai , Hoon Hong , Bican Xia

The notion of random sequence was introduced by Martin-Loef in 1966. At the same time he defined the so-called randomness deficiency function that shows how close are random sequences to non-random (in some natural sense). Other deficiency…

Logic · Mathematics 2016-08-31 Gleb Novikov

A common statistical task lies in showing asymptotic normality of certain statistics. In many of these situations, classical textbook results on weak convergence theory suffice for the problem at hand. However, there are quite some…

Probability · Mathematics 2019-03-26 Viktor Bengs , Hajo Holzmann

This paper studies the important problem of quantum classification of Boolean functions from a entirely novel perspective. Typically, quantum classification algorithms allow us to classify functions with a probability of $1.0$, if we are…

Random features are a powerful technique for rewriting positive-definite kernels as linear products. They bring linear tools to bear in important nonlinear domains like KNNs and attention. Unfortunately, practical implementations require…

Machine Learning · Computer Science 2024-10-25 Luke Sernau , Silvano Bonacina , Rif A. Saurous

Kleene algebra (KA) is an important tool for reasoning about general program equivalences, with a decidable and complete equational theory. However, KA cannot always prove equivalences between specific programs. For this purpose, one adds…

Programming Languages · Computer Science 2026-01-21 Liam Chung , Tobias Kappé

A compression function is a map that slims down an observational set into a subset of reduced size, while preserving its informational content. In multiple applications, the condition that one new observation makes the compressed set change…

Machine Learning · Computer Science 2024-01-09 Marco C. Campi , Simone Garatti

We propose a novel definition of Shapley values with uncertain value functions based on first principles using probability theory. Such uncertain value functions can arise in the context of explainable machine learning as a result of…

Machine Learning · Computer Science 2023-04-03 Raoul Heese , Sascha Mücke , Matthias Jakobs , Thore Gerlach , Nico Piatkowski

The correlation function in quantum systems plays a vital role in decoding their properties and gaining insights into physical phenomena. Its interpretation corresponds to the propagation of particle excitations between space-time, similar…

Quantum Physics · Physics 2024-05-14 Yuan Feng , Xi Chen , Yongcheng Ding

It is well known that any projective measurement can be decomposed into a sequence of weak measurements, which cause only small changes to the state. Similar constructions for generalized measurements, however, have relied on the use of an…

Quantum Physics · Physics 2008-08-24 Ognyan Oreshkov , Todd A. Brun

Mathematicians has been trying to prove the weak Goldbach's conjecture by adding prime numbers, as stated in the conjecture. However, we believe that the solution does not need to be analytically solved. Instead of trying to add prime…

General Mathematics · Mathematics 2012-07-10 Luis A. Mateos

Weak measurements offer new insights into the behavior of quantum systems. Combined with post-selection, quantum mechanics predicts a range of new experimentally testable phenomena. In this paper I consider weak measurements performed on…

Quantum Physics · Physics 2009-11-13 P. C. W. Davies

Finite automata whose computations can be reversed, at any point, by knowing the last k symbols read from the input, for a fixed k, are considered. These devices and their accepted languages are called k-reversible automata and k-reversible…

Formal Languages and Automata Theory · Computer Science 2017-08-23 Giovanna J. Lavado , Giovanni Pighizzini , Luca Prigioniero

Weakly recognizing morphisms from free semigroups onto finite semigroups are a classical way for defining the class of omega-regular languages, i.e., a set of infinite words is weakly recognizable by such a morphism if and only if it is…

Formal Languages and Automata Theory · Computer Science 2016-04-28 Lukas Fleischer , Manfred Kufleitner
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