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As one of the most significant models, the uniform recursive tree (URT) has found many applications in a variety of fields. In this paper, we study rigorously the structural features and spectral properties of the adjacency matrix for a…

Statistical Mechanics · Physics 2009-04-02 Yi Qi , Zhongzhi Zhang , Bailu Ding , Shuigeng Zhou , Jihong Guan

We investigate the number of permutations that occur in random labellings of trees. This is a generalisation of the number of subpermutations occurring in a random permutation. It also generalises some recent results on the number of…

Probability · Mathematics 2022-12-22 Michael Albert , Cecilia Holmgren , Tony Johansson , Fiona Skerman

We present an algorithm for arc reversal in Bayesian networks with tree-structured conditional probability tables, and consider some of its advantages, especially for the simulation of dynamic probabilistic networks. In particular, the…

Artificial Intelligence · Computer Science 2013-02-08 Adrian Y. W. Cheuk , Craig Boutilier

We consider the tributary structure of Howard's drainage model studied by Gangopadhyay et. al. Conditional on the event that the tributary survives up to time $n$, we show that, as a sequence of random metric spaces, scaled tributary…

Probability · Mathematics 2020-08-11 Kumarjit Saha

The successive discrete structures generated by a sequential algorithm from random input constitute a Markov chain that may exhibit long term dependence on its first few input values. Using examples from random graph theory and search…

Probability · Mathematics 2023-06-22 Rudolf Grübel

Consider the Aldous--Pitman fragmentation process [Ann Probab, 26(4):1703--1726, 1998] of a Brownian continuum random tree ${\cal T}^{\mathrm{br}}$. The associated cut tree cut$({\cal T}^{\mathrm{br}})$, introduced by Bertoin and Miermont…

Probability · Mathematics 2017-10-11 Nicolas Broutin , Minmin Wang

In the critical beta-splitting model of a random $n$-leaf binary tree, leaf-sets are recursively split into subsets, and a set of $m$ leaves is split into subsets containing $i$ and $m-i$ leaves with probabilities proportional to…

Probability · Mathematics 2024-09-09 David Aldous , Boris Pittel

We introduce a non-increasing tree growth process $((T_n,\sigma_n),\, n\ge 1)$, where $T_n$ is a rooted labeled tree on $n$ vertices and ${\sigma}_n$ is a permutation of the vertex labels. The construction of $(T_{n},{\sigma}_n)$ from…

Probability · Mathematics 2021-11-11 Laura Eslava

Knowing the causal structure of a system is of fundamental interest in many areas of science and can aid the design of prediction algorithms that work well under manipulations to the system. The causal structure becomes identifiable from…

Machine Learning · Statistics 2022-03-30 Martin Emil Jakobsen , Rajen D. Shah , Peter Bühlmann , Jonas Peters

We study vantage-point trees constructed using an independent sample from the uniform distribution on a fixed convex body $K$ in $(\mathbb{R}^d,\|\cdot\|)$, where $\|\cdot\|$ is an arbitrary norm on $\mathbb{R}^d$. We prove that a sequence…

Probability · Mathematics 2024-12-23 Congzao Dong , Alexander Marynych , Ilya Molchanov

This paper extends the study of fringe trees in random plane trees with a given degree statistic. While previous work established the asymptotic normality of the count of fringe trees isomorphic to a fixed tree, we investigate the case…

Probability · Mathematics 2026-04-08 Gabriel Berzunza Ojeda , Cecilia Holmgren , Svante Janson

In this paper, we redesign and simplify an algorithm due to Remy et al. for the generation of rooted planar trees that satisfies a given partition of degrees. This new version is now optimal in terms of random bit complexity, up to a…

Discrete Mathematics · Computer Science 2014-01-21 Olivier Bodini , David Julien , Marchal Philippe

Recently proposed budding tree is a decision tree algorithm in which every node is part internal node and part leaf. This allows representing every decision tree in a continuous parameter space, and therefore a budding tree can be jointly…

Machine Learning · Computer Science 2014-12-22 Ozan İrsoy , Ethem Alpaydın

We consider learning the structures of Gaussian latent tree models with vector observations when a subset of them are arbitrarily corrupted. First, we present the sample complexities of Recursive Grouping (RG) and Chow-Liu Recursive…

Machine Learning · Statistics 2021-10-26 Fengzhuo Zhang , Vincent Y. F. Tan

It has been claimed in Aldous, Miermont and Pitman [PTRF, 2004] that all L\'evy trees are mixings of inhomogeneous continuum random trees. We give a rigorous proof of this claim in the case of a stable branching mechanism, relying on a new…

Probability · Mathematics 2022-11-15 Minmin Wang

Aldous, Evans and Pitman (1998) studied the behavior of the fragmentation process derived from deleting the edges of a uniform random tree on $n$ labelled vertices. In particular, they showed that, after proper rescaling, the above…

Probability · Mathematics 2025-09-03 Gabriel Berzunza Ojeda , Cecilia Holmgren

In this paper, new context of Chinese Remainder Theorem (CRT) based analysis of combinatorial sequence generators has been presented. CRT is exploited to establish fixed patterns in LFSR sequences and underlying cyclic structures of finite…

Cryptography and Security · Computer Science 2015-04-07 Muhammad Asad Khan , Amir Ali Khan , Fauzan Mirza

Given $n \in \mathbb{N}$ and $\mu \in \mathbb{R}$, a $\textit{$\mu$-height-biased tree of size $n$}$ is a random plane tree $\mathbf{\mathbf{T}}_n$ with $n$ vertices with law given by $\mathbb{P}(\mathbf{T}=t) \propto e^{-\mu h(t)}$, where…

Probability · Mathematics 2025-12-22 Louigi Addario-Berry , Benoît Corsini , Neeladri Maitra , Meltem Ünel

We define a model for random (abstract) cell complexes (CCs), similiar to the well-known Erd\H{o}s-R\'enyi model for graphs and its extensions for simplicial complexes. To build a random cell complex, we first draw from an Erd\H{o}s-R\'enyi…

Data Structures and Algorithms · Computer Science 2025-11-21 Josef Hoppe , Michael T. Schaub

Variations on a theorem of Cand\`es, Romberg and Tao The CRT theorem reconstructs a signal from a sparse set of frequencies, a paradigm of Compressed sensing. The signal is assumed to be carried by a small number of points, s, in a large…

Classical Analysis and ODEs · Mathematics 2012-10-16 Jean-Pierre Kahane
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