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We consider a probability distribution on the set of Boolean functions in n variables which is induced by random Boolean expressions. Such an expression is a random rooted plane tree where the internal vertices are labelled with connectives…

Combinatorics · Mathematics 2015-09-28 Antoine Genitrini , Bernhard Gittenberger , Veronika Kraus , Cécile Mailler

In this paper we present with algebraic trees a novel notion of (continuum) trees which generalizes countable graph-theoretic trees to (potentially) uncountable structures. For that purpose we focus on the tree structure given by the branch…

Probability · Mathematics 2021-04-29 Wolfgang Löhr , Anita Winter

We consider random binary trees that appear as the output of certain standard algorithms for sorting and searching if the input is random. We introduce the subtree size metric on search trees and show that the resulting metric spaces…

Probability · Mathematics 2014-05-06 Rudolf Grübel

We study probability distributions over free algebras of trees. Probability distributions can be seen as particular (formal power) tree series [Berstel et al 82, Esik et al 03], i.e. mappings from trees to a semiring K . A widely studied…

Machine Learning · Computer Science 2008-07-21 François Denis , Amaury Habrard , Rémi Gilleron , Marc Tommasi , Édouard Gilbert

Let $(X,\tau)$ be a Polish space with Borel probability measure $\mu,$ and $G$ a locally finite one-ended Borel graph on $X.$ We show that $G$ admits a Borel one-ended spanning tree generically. If $G$ is induced by a free Borel action of…

Combinatorics · Mathematics 2022-10-27 Matthew Bowen , Antoine Poulin , Jenna Zomback

We consider the space of complete and separable metric spaces which are equipped with a probability measure. A notion of convergence is given based on the philosophy that a sequence of metric measure spaces converges if and only if all…

Probability · Mathematics 2008-06-13 Andreas Greven , Peter Pfaffelhuber , Anita Winter

Coloured probability tree models are statistical models coding conditional independence between events depicted in a tree graph. They are more general than the very important class of context-specific Bayesian networks. In this paper, we…

Statistics Theory · Mathematics 2020-06-16 Eliana Duarte , Christiane Görgen

The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is…

Machine Learning · Statistics 2022-03-24 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

We consider the problem of computing the measure of a regular set of infinite binary trees. While the general case remains unsolved, we show that the measure of a language can be computed when the set is given in one of the following three…

Formal Languages and Automata Theory · Computer Science 2020-02-03 Marcin Przybyłko , Michał Skrzypczak

We show that if a strictly positive joint probability distribution for a set of binary random variables factors according to a tree, then vertex separation represents all and only the independence relations enclosed in the distribution. The…

Artificial Intelligence · Computer Science 2013-01-18 Ann Becker , Dan Geiger , Christopher Meek

With the algebraic trees, L\"ohr and Winter (2021) introduced a generalization of the notion of graph-theoretic trees to account for potentially uncountable structures. The tree structure is given by the map which assigns to each triple of…

Probability · Mathematics 2022-08-01 Josué Nussbaumer , Viet Chi Tran , Anita Winter

We study the probability measure $\mu_{0}$ for which the moment sequence is $\binom{3n}{n}\frac{1}{n+1}$. We prove that $\mu_{0}$ is absolutely continuous, find the density function and prove that $\mu_{0}$ is infinitely divisible with…

Probability · Mathematics 2013-12-12 Wojciech Mlotkowski , Karol A. Penson

We consider fixed-point equations for probability measures charging measured compact metric spaces that naturally yield continuum random trees. On the one hand, we study the existence/uniqueness of the fixed-points and the convergence of…

Probability · Mathematics 2021-05-05 Nicolas Broutin , Henning Sulzbach

Probability estimation is one of the fundamental tasks in statistics and machine learning. However, standard methods for probability estimation on discrete objects do not handle object structure in a satisfactory manner. In this paper, we…

Applications · Statistics 2018-11-06 Cheng Zhang , Frederick A. Matsen

A causal set is a countably infinite poset in which every element is above finitely many others; causal sets are exactly the posets that have a linear extension with the order-type of the natural numbers -- we call such a linear extension a…

Combinatorics · Mathematics 2012-01-31 Graham Brightwell , Malwina Luczak

We investigate the geography of Hilbert schemes parametrizing closed subschemes of projective space with specified Hilbert polynomials. We classify Hilbert schemes with unique Borel-fixed points via combinatorial expressions for their…

Algebraic Geometry · Mathematics 2020-07-28 Andrew P. Staal

Tree sets are posets with additional structure that generalize tree-like objects in graphs, matroids, or other combinatorial structures. They are a special class of abstract separation systems. We study infinite tree sets and how they…

Combinatorics · Mathematics 2025-05-16 Jay Lilian Kneip

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

In this paper, we address the problem of constructing a uniform probability measure on $\mathbb{N}$. Of course, this is not possible within the bounds of the Kolmogorov axioms and we have to violate at least one axiom. We define a…

Probability · Mathematics 2017-02-02 Timber Kerkvliet , Ronald Meester

A cluster tree provides a highly-interpretable summary of a density function by representing the hierarchy of its high-density clusters. It is estimated using the empirical tree, which is the cluster tree constructed from a density…

Statistics Theory · Mathematics 2017-02-14 Jisu Kim , Yen-Chi Chen , Sivaraman Balakrishnan , Alessandro Rinaldo , Larry Wasserman
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