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Pairwise ordered tree alignment are combinatorial objects that appear in RNA secondary structure comparison. However, the usual representation of tree alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce identical…

Quantitative Methods · Quantitative Biology 2016-03-08 Cedric Chauve , Julien Courtiel , Yann Ponty

In graph theory, a tree is one of the more popular families of graphs with a wide range of applications in computer science as well as many other related fields. While there are several distance measures over the set of all trees, we…

Information Theory · Computer Science 2021-02-04 Lev Yohananov , Eitan yaakobi

We study the leaf-to-leaf distances on full and complete m-ary graphs using a recursive approach. In our formulation, leaves are ordered along a line. We find explicit analytical formulae for the sum of all paths for arbitrary leaf-to-leaf…

Mathematical Physics · Physics 2015-10-12 Andrew M. Goldsborough , S. Alex Rautu , Rudolf A. Römer

Supertree methods are tree reconstruction techniques that combine several smaller gene trees (possibly on different sets of species) to build a larger species tree. The question of interest is whether the reconstructed supertree converges…

Populations and Evolution · Quantitative Biology 2021-05-06 Lam Si Tung Ho , Vu Dinh

Rooted, weighted continuum random trees are used to describe limits of sequences of random discrete trees. Formally, they are random quadruples $(\mathcal{T},d,r,p)$, where $(\mathcal{T},d)$ is a tree-like metric space, $r\in\mathcal{T}$ is…

Probability · Mathematics 2021-01-29 Noah Forman

The path-difference metric is one of the oldest distances for the comparison of fully resolved phylogenetic trees, but its statistical properties are still quite unknown. In this paper we compute the mean value of the square of the…

Populations and Evolution · Quantitative Biology 2009-06-16 Arnau Mir , Francesc Rossello

This paper presents a generalization of the Wasserstein distance for both persistence diagrams and merge trees [20], [66] that takes advantage of the regions of their topological features in the input domain. Specifically, we redefine the…

Graphics · Computer Science 2025-10-21 Mathieu Pont , Christoph Garth

Model performance is frequently reported only for the overall population under consideration. However, due to heterogeneity, overall performance measures often do not accurately represent model performance within specific subgroups. We…

Methodology · Statistics 2025-06-03 Ruotao Zhang , Constantine Gatsonis , Jon Steingrimsson

In a recent article by M. Bona and A. Vince, the authors introduced the concept of an assembly tree for a graph. Assembly trees act as record keeping devices for the construction of a given graph from its vertices. In this paper we extend…

Combinatorics · Mathematics 2019-01-29 Aria Dougherty , Nick Mayers , Robert Short

The interleaving distance is arguably the most widely used metric in topological data analysis (TDA) due to its applicability to a wide array of inputs of interest, such as (multiparameter) persistence modules, Reeb graphs, merge trees, and…

Algebraic Topology · Mathematics 2026-01-15 Astrid A. Olave , Elizabeth Munch

We provide a proximal average with repect to a $1$-coercive Legendre function. In the sense of Bregman distance, the Bregman envelope of the proximal average is a convex combination of Bregman envelopes of individual functions. The Bregman…

Optimization and Control · Mathematics 2022-02-25 Xianfu Wang , Heinz H. Bauschke

This paper presents a distance function between sets based on an average of distances between their elements. The distance function is a metric if the sets are non-empty finite subsets of a metric space. It can be applied to produce various…

Metric Geometry · Mathematics 2011-09-13 Osamu Fujita

The general communication tree embedding problem is the problem of mapping a set of communicating terminals, represented by a graph G, into the set of vertices of some physical network represented by a tree T. In the case where the vertices…

Computational Complexity · Computer Science 2016-01-13 Saber Mirzaei

The reliability of a phylogenetic inference method from genomic sequence data is ensured by its statistical consistency. Bayesian inference methods produce a sample of phylogenetic trees from the posterior distribution given sequence data.…

Metric Geometry · Mathematics 2016-06-10 Alex Gavryushkin , Alexei J. Drummond

Ultrametric trees are trees whose leaves lie at the same distance from the root. They are used to model the genealogy of a population of particles co-existing at the same point in time. We show how the boundary of an ultrametric tree, like…

Probability · Mathematics 2017-02-28 Amaury Lambert

Given two binary trees on $N$ labeled leaves, the quartet distance between the trees is the number of disagreeing quartets. By permuting the leaves at random, the expected quartets distance between the two trees is…

Combinatorics · Mathematics 2021-01-01 Benny Chor , Péter L. Erdős , Yonatan Komornik

We consider the biased random walk on a tree constructed from the set of finite self-avoiding walks on a lattice, and use it to construct probability measures on infinite self-avoiding walks. The limit measure (if it exists) obtained when…

Probability · Mathematics 2019-12-25 Vincent Beffara , Cong Bang Huynh

We determine the maximum distance between any two of the center, centroid, and subtree core among trees with a given order. Corresponding results are obtained for trees with given maximum degree and also for trees with given diameter. The…

Combinatorics · Mathematics 2017-01-20 Heather Smith , László Székely , Hua Wang , Shuai Yuan

Recursive partitioning is the core of several statistical methods including CART, random forest, and boosted trees. Despite the popularity of tree based methods, to date, there did not exist methods for combining multiple trees into a…

Data Structures and Algorithms · Computer Science 2016-03-18 Sean Skwerer , Heping Zhang

Metric learning has the aim to improve classification accuracy by learning a distance measure which brings data points from the same class closer together and pushes data points from different classes further apart. Recent research has…

Machine Learning · Computer Science 2018-05-21 Benjamin Paaßen
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