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It is well known that to estimate the Shannon entropy for symbolic sequences accurately requires a large number of samples. When some aspects of the data are known it is plausible to attempt to use this to more efficiently compute entropy.…

Data Analysis, Statistics and Probability · Physics 2018-05-18 Andrew D. Back , Daniel Angus , Janet Wiles

The method is introduced for fast data processing by reducing the probability amplitudes of undesirable elements. The algorithm has a mathematical description and circuit implementation on a quantum processor. The idea is to make a quick…

Quantum Physics · Physics 2025-04-24 Karina Zakharova , Artem Chernikov , Sergey Sysoev

A method for analyzing sequential data sets, similar to the permutation entropy one, is discussed. The characteristic features of this method are as follows: it preserves information about equal values, if any, in the embedding vectors; it…

Data Analysis, Statistics and Probability · Physics 2023-06-16 Alexander Vidybida

We exploit and clarify the use of random matrix theory for the calculation of the entanglement entropy of free Fermi gases. We apply this method to obtain analytic predictions for Renyi entanglement entropies of a one-dimensional gas…

Statistical Mechanics · Physics 2015-01-08 Pasquale Calabrese , Pierre Le Doussal , Satya N. Majumdar

The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions, thus has been widely adopted in numerous statistical…

Machine Learning · Statistics 2022-05-17 Yuxin Dong , Tieliang Gong , Shujian Yu , Chen Li

In the ordinal Matroid Secretary Problem (MSP), elements from a weighted matroid are presented in random order to an algorithm that must incrementally select a large weight independent set. However, the algorithm can only compare pairs of…

Data Structures and Algorithms · Computer Science 2018-02-07 José A. Soto , Abner Turkieltaub , Victor Verdugo

We propose practical algorithms for entrywise $\ell_p$-norm low-rank approximation, for $p = 1$ or $p = \infty$. The proposed framework, which is non-convex and gradient-based, is easy to implement and typically attains better…

Machine Learning · Computer Science 2018-05-25 Anastasios Kyrillidis

In many high-impact applications, it is important to ensure the quality of output of a machine learning algorithm as well as its reliability in comparison with the complexity of the algorithm used. In this paper, we have initiated a…

Machine Learning · Computer Science 2023-03-03 Katarina Doctor , Tong Mao , Hrushikesh Mhaskar

Schemes for exact multiplication of small matrices have a large symmetry group. This group defines an equivalence relation on the set of multiplication schemes. There are algorithms to decide whether two schemes are equivalent. However, for…

Computational Complexity · Computer Science 2022-06-02 Manuel Kauers , Jakob Moosbauer

Comparison-based algorithms are algorithms for which the execution of each operation is solely based on the outcome of a series of comparisons between elements. Comparison-based computations can be naturally represented via the following…

Data Structures and Algorithms · Computer Science 2020-11-17 Michel Schellekens

The evaluation of the probability of union of a large number of independent events requires several combinations involving the factorial and the use of high performance computers with several hours of processing. Bounds and simplifications…

Numerical Analysis · Mathematics 2025-03-07 Edson Luiz Ursini , Paulo S. Martins

This paper shows how to evolve numerically the maximum entropy probability distributions for a given set of constraints, which is a variational calculus problem. An evolutionary algorithm can obtain approximations to some well-known…

Methodology · Statistics 2020-02-07 Raul Rojas

We propose a new algorithm to compute numerically the distribution function of the sum of $d$ dependent, non-negative random variables with given joint distribution.

Statistics Theory · Mathematics 2011-06-16 Philipp Arbenz , Paul Embrechts , Giovanni Puccetti

We study the problem of discovering the simplest latent variable that can make two observed discrete variables conditionally independent. The minimum entropy required for such a latent is known as common entropy in information theory. We…

Given a collection of probability distributions $p_{1},\ldots,p_{m}$, the minimum entropy coupling is the coupling $X_{1},\ldots,X_{m}$ ($X_{i}\sim p_{i}$) with the smallest entropy $H(X_{1},\ldots,X_{m})$. While this problem is known to be…

Information Theory · Computer Science 2021-09-21 Cheuk Ting Li

The problem of determining the joint probability distributions for correlated random variables with pre-specified marginals is considered. When the joint distribution satisfying all the required conditions is not unique, the "most unbiased"…

Statistical Mechanics · Physics 2015-06-12 Hernán Larralde

We study ranked enumeration of join-query results according to very general orders defined by selective dioids. Our main contribution is a framework for ranked enumeration over a class of dynamic programming problems that generalizes…

Databases · Computer Science 2020-09-15 Nikolaos Tziavelis , Deepak Ajwani , Wolfgang Gatterbauer , Mirek Riedewald , Xiaofeng Yang

A common statistical situation concerns inferring an unknown distribution Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m) have a known functional relationship. Most commonly, n<m, and the task is relatively…

Quantitative Methods · Quantitative Biology 2016-02-01 Jayajit Das , Sayak Mukherjee , Susan E. Hodge

We consider distributions of ordered random vectors with given one-dimensional marginal distributions. We give an elementary necessary and sufficient condition for the existence of such a distribution with finite entropy. In this case, we…

Statistics Theory · Mathematics 2015-09-08 Cristina Butucea , Jean-François Delmas , Anne Dutfoy , Richard Fischer

So-called average subsystem entropies are defined by first taking partial traces over some pure state to define density matrices, then calculating the subsystem entropies, and finally averaging over the pure states to define the average…

Quantum Physics · Physics 2017-11-02 Ana Alonso-Serrano , Matt Visser