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Phylogenetic (evolutionary) trees and networks are leaf-labeled graphs that are widely used to represent the evolutionary relationships between entities such as species, languages, cancer cells, and viruses. To reconstruct and analyze…

Data Structures and Algorithms · Computer Science 2023-08-21 Michael J. Dinneen , Pankaj S. Ghodla , Simone Linz

Generally, multi-objective optimisation problems are solved exactly or approximated by solving a series of scalarisations, for example by dichotomic search. In this paper, we take a different approach and attempt to compute the set of all…

Optimization and Control · Mathematics 2026-01-28 Oliver Bachtler , Felix Fritz , Stefan Ruzika

We compare the phylogenetic tensors for various trees and networks for two, three and four taxa. If the probability spaces between one tree or network and another are not identical then there will be phylogenetic tensors that could have…

Populations and Evolution · Quantitative Biology 2016-06-24 Jonathan Mitchell

There are several tools available to infer phylogenetic trees, which depict the evolutionary relationships among biological entities such as viral and bacterial strains in infectious outbreaks, or cancerous cells in tumor progression trees.…

Data Structures and Algorithms · Computer Science 2023-12-22 António Pedro Branco , Cátia Vaz , Alexandre P. Francisco

The metric space of phylogenetic trees defined by Billera, Holmes, and Vogtmann, which we refer to as BHV space, provides a natural geometric setting for describing collections of trees on the same set of taxa. However, it is sometimes…

Populations and Evolution · Quantitative Biology 2018-07-12 Gillian Grindstaff , Megan Owen

Phylogenetic networks are important for the study of evolution. The number of methods to find such networks is increasing, but most such methods can only reconstruct small networks. To find bigger networks, one can attempt to combine small…

Discrete Mathematics · Computer Science 2019-12-10 Remie Janssen , Mark Jones , Yukihiro Murakami

Causal Bayesian networks are widely used tools for summarising the dependencies between variables and elucidating their putative causal relationships. By restricting the search to trees, for example, learning the optimum from data is…

Computation · Statistics 2025-03-10 Felix L. Rios , Giusi Moffa , Jack Kuipers

Internal measures that are used to assess the quality of a clustering usually take into account intra-group and/or inter-group criteria. There are many papers in the literature that propose algorithms with provable approximation guarantees…

Machine Learning · Computer Science 2024-01-17 Eduardo S. Laber , Lucas Murtinho

In many high-dimensional problems,polynomial-time algorithms fall short of achieving the statistical limits attainable without computational constraints. A powerful approach to probe the limits of polynomial-time algorithms is to study the…

Statistics Theory · Mathematics 2025-07-11 Bertrand Even , Christophe Giraud , Nicolas Verzelen

Mixture distributions arise in many parametric and non-parametric settings -- for example, in Gaussian mixture models and in non-parametric estimation. It is often necessary to compute the entropy of a mixture, but, in most cases, this…

Information Theory · Computer Science 2022-11-22 Artemy Kolchinsky , Brendan D. Tracey

Structure and parameters in a Bayesian network uniquely specify the probability distribution of the modeled domain. The locality of both structure and probabilistic information are the great benefits of Bayesian networks and require the…

Artificial Intelligence · Computer Science 2013-01-30 Volker Tresp , Michael Haft , Reimar Hofmann

Least-squares fits are an important tool in many data analysis applications. In this paper, we review theoretical results, which are relevant for their application to data from counting experiments. Using a simple example, we illustrate the…

Data Analysis, Statistics and Probability · Physics 2019-06-07 Hans Dembinski , Michael Schmelling , Roland Waldi

We initiate a systematic study of utilizing predictions to improve over approximation guarantees of classic algorithms, without increasing the running time. We propose a systematic method for a wide class of optimization problems that ask…

Data Structures and Algorithms · Computer Science 2024-11-26 Antonios Antoniadis , Marek Eliáš , Adam Polak , Moritz Venzin

The search for multivariate quadrature rules of minimal size with a specified polynomial accuracy has been the topic of many years of research. Finding such a rule allows accurate integration of moments, which play a central role in many…

Numerical Analysis · Mathematics 2021-05-04 John D. Jakeman , Akil Narayan

This paper introduces constNJ, the first algorithm for phylogenetic reconstruction of sets of trees with constrained pairwise rooted subtree-prune regraft (rSPR) distance. We are motivated by the problem of constructing sets of trees which…

Populations and Evolution · Quantitative Biology 2009-09-30 Frederick A. Matsen

Phylogenetic networks generalize phylogenetic trees by allowing the modelization of events of reticulate evolution. Among the different kinds of phylogenetic networks that have been proposed in the literature, the subclass of binary…

Data Structures and Algorithms · Computer Science 2020-07-01 Gabriel Cardona , Joan Carles Pons , Celine Scornavacca

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

Phylogenetic reconciliation seeks to explain host-symbiont co-evolution by mapping parasite trees onto host trees through events such as cospeciation, duplication, host switching, and loss. Finding an optimal reconciliation that ensures…

Populations and Evolution · Quantitative Biology 2026-02-02 Cyriac Antony , Alessio Martino , Blerina Sinaimeri

Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm. The conventional approach to determining a suitable number of components is to compare…

Applications · Statistics 2014-05-26 Siew Li Tan , David J. Nott

In real life, it is always an urge to reach our goal in minimum effort i.e., it should have a minimum constrained path. The path may be shortest route in practical life, either physical or electronic medium. The scenario is to represents…

Neural and Evolutionary Computing · Computer Science 2014-01-14 Sounak Sadhukhan , Samar Sen Sarma
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