English
Related papers

Related papers: Checking Phylogenetic Decisiveness in Theory and i…

200 papers

Phylogenetic networks are used to represent evolutionary scenarios in biology and linguistics. To find the most probable scenario, it may be necessary to compare candidate networks, to distinguish different networks, and to see when one…

Combinatorics · Mathematics 2020-04-10 Remie Janssen , Yukihiro Murakami

Decision trees (DTs) embody interpretable classifiers. DTs have been advocated for deployment in high-risk applications, but also for explaining other complex classifiers. Nevertheless, recent work has demonstrated that predictions in DTs…

Artificial Intelligence · Computer Science 2022-05-20 Yacine Izza , Alexey Ignatiev , Nina Narodytska , Martin C. Cooper , Joao Marques-Silva

Given a model in algebraic statistics and some data, the likelihood function is a rational function on a projective variety. Algebraic algorithms are presented for computing all critical points of this function, with the aim of identifying…

Statistics Theory · Mathematics 2007-06-13 Serkan Hosten , Amit Khetan , Bernd Sturmfels

We consider the reconstruction of a phylogeny from multiple genes under the multispecies coalescent. We establish a connection with the sparse signal detection problem, where one seeks to distinguish between a distribution and a mixture of…

Probability · Mathematics 2017-07-24 Elchanan Mossel , Sebastien Roch

In this paper we suggest that, under suitable conditions, supervised learning can provide the basis to formulate at the microscopic level quantitative questions on the phenotype structure of multicellular organisms. The problem of…

Molecular Networks · Quantitative Biology 2012-06-14 D. Napoletani , E. Petricoin , D. C. Struppa

In molecular phylogeny, relationships among organisms are reconstructed using DNA or protein sequences and are displayed as trees. A linear increase in the number of sequences results in an exponential increase of possible trees. Thus,…

Genomics · Quantitative Biology 2007-05-23 Kerstin Hoef-Emden

Despite tremendous progress, machine learning and deep learning still suffer from incomprehensible predictions. Incomprehensibility, however, is not an option for the use of (deep) reinforcement learning in the real world, as unpredictable…

Artificial Intelligence · Computer Science 2024-07-23 Manuel Eberhardinger , Florian Rupp , Johannes Maucher , Setareh Maghsudi

A classical result, fundamental to evolutionary biology, states that an edge-weighted tree $T$ with leaf set $X$, positive edge weights, and no vertices of degree 2 can be uniquely reconstructed from the set of leaf-to-leaf distances…

Populations and Evolution · Quantitative Biology 2011-07-15 A. W. M. Dress , K. T. Huber , M. Steel

Phylogenies are commonly used to represent the evolutionary relationships between species, and often these phylogenies are equipped with edge lengths that indicate degrees of evolutionary difference. Given such a phylogeny, a popular…

Populations and Evolution · Quantitative Biology 2025-02-12 Martin Frohn , Kerry Manson

For massive and heterogeneous modern datasets, it is of fundamental interest to provide guarantees on the accuracy of estimation when computational resources are limited. In the application of learning to rank, we provide a hierarchy of…

Machine Learning · Computer Science 2016-08-23 Ashish Khetan , Sewoong Oh

We consider the problem of estimating the evolutionary history of a set of species (phylogeny or species tree) from several genes. It is known that the evolutionary history of individual genes (gene trees) might be topologically distinct…

Populations and Evolution · Quantitative Biology 2016-11-18 Gautam Dasarathy , Robert Nowak , Sebastien Roch

The importance of classifying connections in large graphs has been the motivation for a rich line of work on distributed subgraph finding that has led to exciting recent breakthroughs. A crucial aspect that remained open was whether…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-27 Keren Censor-Hillel , Dean Leitersdorf , David Vulakh

Decision-theoretic troubleshooting is one of the areas to which Bayesian networks can be applied. Given a probabilistic model of a malfunctioning man-made device, the task is to construct a repair strategy with minimal expected cost. The…

Artificial Intelligence · Computer Science 2013-08-02 Václav Lín

For a positive integer $k$, a $k$-colouring of a graph $G=(V,E)$ is a mapping $c: V\rightarrow\{1,2,...,k\}$ such that $c(u)\neq c(v)$ whenever $uv\in E$. The Colouring problem is to decide, for a given $G$ and $k$, whether a $k$-colouring…

Computational Complexity · Computer Science 2016-02-16 Petr A. Golovach , Matthew Johnson , Daniël Paulusma , Jian Song

In this work, we answer an open problem in the study of phylogenetic networks. Phylogenetic trees are rooted binary trees in which all edges are directed away from the root, whereas phylogenetic networks are rooted acyclic digraphs. For the…

Populations and Evolution · Quantitative Biology 2015-11-12 Andreas D. M. Gunawan , Bhaskar DasGupta , Louxin Zhang

Phylogenetic networks are becoming of increasing interest to evolutionary biologists due to their ability to capture complex non-treelike evolutionary processes. From a combinatorial point of view, such networks are certain types of rooted…

Combinatorics · Mathematics 2019-10-21 Katharina T. Huber , Guillaume E. Scholz

The multispecies coalescent process models the genealogical relationships of genes sampled from several species, enabling useful predictions about phenomena such as the discordance between the gene tree and the species phylogeny due to…

Populations and Evolution · Quantitative Biology 2020-12-11 Jakub Truszkowski , Celine Scornavacca , Fabio Pardi

In order to speed-up classification models when facing a large number of categories, one usual approach consists in organizing the categories in a particular structure, this structure being then used as a way to speed-up the prediction…

Machine Learning · Computer Science 2015-11-26 Aurélia Léon , Ludovic Denoyer

Decision trees are a popular family of models due to their attractive properties such as interpretability and ability to handle heterogeneous data. Concurrently, missing data is a prevalent occurrence that hinders performance of machine…

Machine Learning · Computer Science 2020-07-01 Pasha Khosravi , Antonio Vergari , YooJung Choi , Yitao Liang , Guy Van den Broeck

In many situations, the decision maker observes items in sequence and needs to determine whether or not to retain a particular item immediately after it is observed. Any decision rule creates a set of items that are selected. We consider…

Probability · Mathematics 2007-05-23 Abba M. Krieger , Moshe Pollak , Ester Samuel-Cahn