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In this paper, we mainly discuss some generalized metric properties and the character of the free paratopological groups, and extend several results valid for free topological groups to free paratopological groups.

General Topology · Mathematics 2013-02-19 Fucai Lin

Asymptotic properties of finitely generated subgroups of free groups, and of finite group presentations, can be considered in several fashions, depending on the way these objects are represented and on the distribution assumed on these…

Group Theory · Mathematics 2018-04-25 Frédérique Bassino , Cyril Nicaud , Pascal Weil

We propose a new method for the calculation of the statistical properties, as e.g. the entropy, of unknown generators of symbolic sequences. The probability distribution $p(k)$ of the elements $k$ of a population can be approximated by the…

chao-dyn · Physics 2009-10-28 Thorsten Pöschel , Werner Ebeling , Helge Rosé

We introduce and study a remarkable family of real probability measures $\pi_{st}$, that we call free Bessel laws. These are related to the free Poisson law $\pi$ via the formulae $\pi_{s1}=\pi^{\boxtimes s}$ and $\pi_{1t}=\pi^{\boxplus…

Probability · Mathematics 2019-02-27 Teodor Banica , Serban Belinschi , Mireille Capitaine , Benoit Collins

Given a universe of discourse X-a domain of possible outcomes-an experiment may consist of selecting one of its elements, subject to the operation of chance, or of observing the elements, subject to imprecision. A priori uncertainty about…

Artificial Intelligence · Computer Science 2013-03-26 Arthur Ramer

The idea underlying the modal formulation of density-based clustering is to associate groups with the regions around the modes of the probability density function underlying the data. This correspondence between clusters and dense regions…

Social and Information Networks · Computer Science 2021-01-22 Giovanna Menardi , Domenico De Stefano

Many AI researchers argue that probability theory is only capable of dealing with uncertainty in situations where a full specification of a joint probability distribution is available, and conclude that it is not suitable for application in…

Artificial Intelligence · Computer Science 2013-04-05 Linda C. van der Gaag

Random number generators are widely used in practical algorithms. Examples include simulation, number theory (primality testing and integer factorization), fault tolerance, routing, cryptography, optimization by simulated annealing, and…

Data Structures and Algorithms · Computer Science 2010-04-21 Richard P. Brent

The definition of conditional probability in case of continuous distributions was an important step in the development of mathematical theory of probabilities. How can we define this notion in algorithmic probability theory? In this survey…

Logic · Mathematics 2016-07-15 Bruno Bauwens , Alexander Shen , Hayato Takahashi

Consider a very large (infinite) population of items, where each item independent from the others is defective with probability p, or good with probability q=1-p. The goal is to identify N good items as quickly as possible. The following…

Other Statistics · Statistics 2018-04-17 Yaakov Malinovsky

The group testing problem is concerned with identifying a small set of infected individuals in a large population. At our disposal is a testing procedure that allows us to test several individuals together. In an idealized setting, a test…

Information Theory · Computer Science 2023-09-19 Oliver Gebhard , Oliver Johnson , Philipp Loick , Maurice Rolvien

Providing generalization guarantees for stochastic optimization algorithms remains a key challenge in learning theory. Recently, numerous works demonstrated the impact of the geometric properties of optimization trajectories on…

Machine Learning · Computer Science 2026-01-23 Mario Tuci , Lennart Bastian , Benjamin Dupuis , Nassir Navab , Tolga Birdal , Umut Şimşekli

We show on theoretical grounds that, even in the presence of noise, probabilistic measurement strategies (which have a certain probability of failure or abstention) can provide, upon a heralded successful outcome, estimates with a precision…

Quantum Physics · Physics 2016-10-27 J. Calsamiglia , B. Gendra , R. Munoz-Tapia , E. Bagan

The concept of complexity appears in virtually all areas of knowledge. Its intuitive meaning shares similarities across fields, but disagreements between its details hinders a general definition, leading to a plethora of proposed…

Statistical Mechanics · Physics 2023-10-04 Roberto C. Alamino

The 'degree of k-step nilpotence' of a finite group G is the proportion of the tuples (x_1,...,x_{k+1}) in G^{k+1} for which the simple commutator [x_1,...,x_{k+1}] is equal to the identity. In this paper we study versions of this for an…

Group Theory · Mathematics 2025-12-04 Armando Martino , Matthew Tointon , Motiejus Valiunas , Enric Ventura

A subset $X$ of a groupoid is said to be deficient if $|X \cdot X|\leq |X|$. It is well-known that the probability that a random groupoid has a deficient $t$-element set with $t\geq 3$ is zero. However, as conjectured in [4], we show that…

Group Theory · Mathematics 2024-07-25 Carles Cardó

For each positive integer n this paper considers a one-parameter family of complex-valued measures on the symmetric group S_n, depending on a complex parameter z. For parameter values z=p^f a prime power, this measure describes splitting…

Number Theory · Mathematics 2018-01-18 Jeffrey C. Lagarias

We propose a new interpretation of measures of information and disorder by connecting these concepts to group theory in a new way. Entropy and group theory are connected here by their common relation to sets of permutations. A combinatorial…

Information Theory · Computer Science 2019-11-25 David J. Galas

In this paper, we introduce a new function related to the sum of element orders of finite groups. It is used to give some criteria for a finite group to be cyclic, abelian, nilpotent, supersolvable and solvable, respectively.

Group Theory · Mathematics 2019-04-09 Marius Tărnăuceanu

Based on existing ideas in the field of imprecise probabilities, we present a new approach for assessing the reliability of the individual predictions of a generative probabilistic classifier. We call this approach robustness…

Machine Learning · Computer Science 2025-04-11 Adrián Detavernier , Jasper De Bock
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