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The need to estimate a particular quantile of a distribution is an important problem which frequently arises in many computer vision and signal processing applications. For example, our work was motivated by the requirements of many…

Data Structures and Algorithms · Computer Science 2014-11-11 Ognjen Arandjelovic , Duc-Son Pham , Svetha Venkatesh

A change point detection procedure using the method of moment estimators is proposed. The test statistics is based on a suitable $Z$-process. The asymptotic behavior of this process is established under both the null and the alternative…

Statistics Theory · Mathematics 2020-10-08 Ilia Negri , Yoichi Nishiyama

There exists, in general, a convex set of quantum state estimators that maximize the likelihood for informationally incomplete data. We propose an estimation scheme, catered to measurement data of this kind, to search for the exact…

Entropy regularization is known to improve exploration in sequential decision-making problems. We show that this same mechanism can also lead to nearly unbiased and lower-variance estimates of the mean reward in the optimize-and-estimate…

Machine Learning · Computer Science 2022-08-26 Ben Chugg , Peter Henderson , Jacob Goldin , Daniel E. Ho

The estimation of an f-divergence between two probability distributions based on samples is a fundamental problem in statistics and machine learning. Most works study this problem under very weak assumptions, in which case it is provably…

Machine Learning · Statistics 2019-10-25 Paul K. Rubenstein , Olivier Bousquet , Josip Djolonga , Carlos Riquelme , Ilya Tolstikhin

Entropy is a measure of the randomness of a system. Estimating the entropy of a quantum state is a basic problem in quantum information. In this paper, we introduce a time-efficient quantum approach to estimating the von Neumann entropy…

Quantum Physics · Physics 2025-12-02 Qisheng Wang , Zhicheng Zhang

Let $A$ and $B$ be two accretive operators. We first introduce the weighted geometric mean of $A$ and $B$ together with some related properties. Afterwards, we define the relative entropy as well as the Tsallis entropy of $A$ and $B$. The…

Functional Analysis · Mathematics 2021-07-23 M. Raïssouli , M. S. Moslehian , S. Furuichi

The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak…

Probability · Mathematics 2015-06-22 Jin-Li Guo , Qi Suo

Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. For descriptive statistical problems such as estimating the N-gram entropy of English language text, a common approach is to use as much data…

Information Theory · Computer Science 2018-05-24 Andrew D. Back , Daniel Angus , Janet Wiles

Entropy estimation plays a significant role in biology, economics, physics, communication engineering and other disciplines. It is increasingly used in software engineering, e.g. in software confidentiality, software testing, predictive…

Information Theory · Computer Science 2025-01-22 Ilaria Pia la Torre , David A. Kelly , Hector D. Menendez , David Clark

Recently, there has been growing attention to study uncertainty measures for doubly truncated random variables. In this paper, the concept of varextropy for doubly truncated random variables is introduced. The changes of this measure under…

Statistics Theory · Mathematics 2024-08-01 Raheleh Zamini , Somayeh Ghafouri , Faranak Goodarzi

The coincidence method of measuring the entropy of a system, proposed some time ago by Ma, is generalized to include systems out of equilibrium. It is suggested that the method can be adapted to analyze multiparticle states produced in…

High Energy Physics - Phenomenology · Physics 2009-10-31 A. Bialas , W. Czyz

We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. This allows us to calculate the complexity of phenomena for which distributions are known. We…

Adaptation and Self-Organizing Systems · Physics 2016-04-01 Guillermo Santamaría-Bonfil , Nelson Fernández , Carlos Gershenson

The notion of matrix entropy was introduced by Tropp and Chen with the aim of measuring the fluctuations of random matrices. It is a certain entropy functional constructed from a representing function with prescribed properties, and Tropp…

Mathematical Physics · Physics 2015-09-25 Frank Hansen , Zhihua Zhang

The invariants of an attractor have been the most used resource to characterize a nonlinear dynamics. Their estimation is a challenging endeavor in short-time series and/or in presence of noise. In this article we present two new…

Chaotic Dynamics · Physics 2017-12-13 Juan F. Restrepo , Gastón Schlotthauer

We introduce the concept of inflation word entropy for random substitutions with a constant and primitive substitution matrix. Previous calculations of the topological entropy of such systems implicitly used this concept and established…

Dynamical Systems · Mathematics 2020-04-15 Philipp Gohlke

Information theoretic quantities are extremely useful in discovering relationships between two or more data sets. One popular method---particularly for continuous systems---for estimating these quantities is the nearest neighbour…

Computation · Statistics 2017-10-19 Joshua Brown , Terry Bossomaier , Lionel Barnett

This paper considers the estimation of Shannon entropy for discrete distributions with countably infinite support. While minimax rates for finite-support distributions are established, infinite-support distributions present distinct…

Statistics Theory · Mathematics 2025-12-03 Octavio César Mesner

The concepts of variability and uncertainty, both epistemic and alleatory, came from experience and coexist with different connotations. Therefore this article attempts to express their relation by analytic means firstly setting sights on…

Other Statistics · Statistics 2013-01-15 Kalman Ziha

Estimating the effect of treatments from natural experiments, where treatments are pre-assigned, is an important and well-studied problem. We introduce a novel natural experiment dataset obtained from an early childhood literacy nonprofit.…

Machine Learning · Statistics 2024-09-10 R. Teal Witter , Christopher Musco