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Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two…

Statistical Mechanics · Physics 2013-01-17 Zhongzhi Zhang , Tong Shan , Guanrong Chen

Recombining trinomial trees are a workhorse for modeling discrete-event systems in option pricing, logistics, and feedback control. Because each node stores a state-dependent quantity, a depth-$D$ tree naively yields $\mathcal{O}(3^{D})$…

Data Structures and Algorithms · Computer Science 2025-10-06 Ethan Torres , Ramavarapu Sreenivas , Richard Sowers

We propose a tree-based algorithm for classification and regression problems in the context of functional data analysis, which allows to leverage representation learning and multiple splitting rules at the node level, reducing…

Machine Learning · Statistics 2020-11-03 Edoardo Belli , Simone Vantini

In this paper we study binary trees with choosable edge lengths, in particular rooted binary trees with the property that the two edges leading from every non-leaf to its two children are assigned integral lengths $l_1$ and $l_2$ with…

Information Theory · Computer Science 2016-08-08 Jens Maßberg

For an additive submonoid $\mathcal{M}$ of $\mathbb{R}_{\ge 0}$, the weight of an $\mathcal{M}$-labeled directed graph is the sum of all of its edge labels, while the content is the product of the labels. Having fixed $\mathcal{M}$ and a…

Combinatorics · Mathematics 2020-04-24 Alexandru Chirvasitu

We study the behavior of untrained neural networks whose weights and biases are randomly distributed using mean field theory. We show the existence of depth scales that naturally limit the maximum depth of signal propagation through these…

Machine Learning · Statistics 2017-04-06 Samuel S. Schoenholz , Justin Gilmer , Surya Ganguli , Jascha Sohl-Dickstein

Starting with Tukey's pioneering work in the 1970's, the notion of depth in statistics has been widely extended especially in the last decade. These extensions include high dimensional data, functional data, and manifold-valued data. In…

Statistics Theory · Mathematics 2020-11-24 Alejandro Cholaquidis , Ricardo Fraiman , Fabrice Gamboa , Leonardo Moreno

In 1989 Erd\H{o}s and Sz\'ekely showed that there is a bijection between (i) the set of rooted trees with $n+1$ vertices whose leaves are bijectively labeled with the elements of $[\ell]=\{1,2,\dots,\ell\}$ for some $\ell \leq n$, and (ii)…

Discrete Mathematics · Computer Science 2025-10-29 Vincent Moulton , Andreas Spillner

A spanning tree of a network or graph is a subgraph that connects all nodes with the least number or weight of edges. The spanning tree is one of the most straightforward techniques for network simplification and sampling, and for…

Social and Information Networks · Computer Science 2025-12-03 Lovro Šubelj

An {\em ancestry labeling scheme} labels the nodes of any tree in such a way that ancestry queries between any two nodes in a tree can be answered just by looking at their corresponding labels. The common measure to evaluate the quality of…

Data Structures and Algorithms · Computer Science 2009-02-19 Pierre Fraigniaud , Amos Korman

We introduce and analyze a random tree model associated to Hoppe's urn. The tree is built successively by adding nodes to the existing tree when starting with the single root node. In each step a node is added to the tree as a child of an…

Probability · Mathematics 2012-07-06 Kevin Leckey , Ralph Neininger

We study the problem of modeling multiple symmetric, weighted networks defined on a common set of nodes, where networks arise from different groups or conditions. We propose a model in which each network is expressed as the sum of a shared…

Statistics Theory · Mathematics 2025-06-23 Hao Yan , Keith Levin

We investigate hide-and-seek games on complex networks using a random walk framework. Specifically, we investigate the efficiency of various degree-biased random walk search strategies to locate items that are randomly hidden on a subset of…

Physics and Society · Physics 2019-02-20 Shubham Pandey , Reimer Kuehn

We present a concept called the branch-depth of a connectivity function, that generalizes the tree-depth of graphs. Then we prove two theorems showing that this concept aligns closely with the notions of tree-depth and shrub-depth of graphs…

Combinatorics · Mathematics 2020-11-05 Matt DeVos , O-joung Kwon , Sang-il Oum

The load of a node in a network is the total traffic going through it when every node pair sustains a uniform bidirectional traffic between them on shortest paths. We show that nodal load can be expressed in terms of the more elementary…

Statistical Mechanics · Physics 2008-04-18 Elias Bareinboim , Valmir C. Barbosa

A rooted arborescence of a directed graph is a spanning tree directed towards a particular vertex. A recent work of Chepuri et al. showed that the arborescences of a covering graph of a directed graph G are closely related to the…

Combinatorics · Mathematics 2025-06-06 Muchen Ju , Junjie Ni , Kaixin Wang , Yihan Xiao

In many studies, it is common to use binary (i.e., unweighted) edges to examine networks of entities that are either adjacent or not adjacent. Researchers have generalized such binary networks to incorporate edge weights, which allow one to…

Physics and Society · Physics 2024-02-29 Lucas Böttcher , Mason A. Porter

In this paper, we study the joint behaviour of the degree, depth and label of and graph distance between high-degree vertices in the random recursive tree. We generalise the results obtained by Eslava and extend these to include the labels…

Probability · Mathematics 2023-01-31 Bas Lodewijks

We define, analyze, and give efficient algorithms for two kinds of distance measures for rooted and unrooted phylogenies. For rooted trees, our measures are based on the topologies the input trees induce on triplets; that is, on…

Data Structures and Algorithms · Computer Science 2009-06-30 Mukul S. Bansal , Jianrong Dong , David Fernández-Baca

The performance of deep neural networks scales with dataset size and label quality, rendering the efficient mitigation of low-quality data annotations crucial for building robust and cost-effective systems. Existing strategies to address…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Francesco Di Salvo , Sebastian Doerrich , Ines Rieger , Christian Ledig