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In many applications, a large number of features are collected with the goal to identify a few important ones. Sometimes, these features lie in a metric space with a known distance matrix, which partially reflects their co-importance…

Methodology · Statistics 2021-09-28 Xuechan Li , Anthony Sung , Jichun Xie

Phylogenetic networks extend phylogenetic trees to model non-vertical inheritance, by which a lineage inherits material from multiple parents. The computational complexity of estimating phylogenetic networks from genome-wide data with…

Populations and Evolution · Quantitative Biology 2022-06-28 Jingcheng Xu , Cécile Ané

In many interesting cases the reconstruction of a correct phylogeny is blurred by high mutation rates and/or horizontal transfer events. As a consequence a divergence arises between the true evolutionary distances and the differences…

Populations and Evolution · Quantitative Biology 2010-02-08 F. Tria , E. Caglioti , V. Loreto , A. Pagnani

Recent works have shown that deep metric learning algorithms can benefit from weak supervision from another input modality. This additional modality can be incorporated directly into the popular triplet-based loss function as distances.…

Computer Vision and Pattern Recognition · Computer Science 2020-06-29 Istvan Fehervari , Ives Macedo

The problem of similarity search is one of the main problems in computer science. This problem has many applications in text-retrieval, web search, computational biology, bioinformatics and others. Similarity between two data objects can be…

Neural and Evolutionary Computing · Computer Science 2013-12-06 Muhammad Marwan Muhammad Fuad

The presence of reticulate evolutionary events in phylogenies turn phylogenetic trees into phylogenetic networks. These events imply in particular that there may exist multiple evolutionary paths from a non-extant species to an extant one,…

Populations and Evolution · Quantitative Biology 2008-03-21 Gabriel Cardona , Merce Llabres , Francesc Rossello , Gabriel Valiente

Distance metric learning (DML) approaches learn a transformation to a representation space where distance is in correspondence with a predefined notion of similarity. While such models offer a number of compelling benefits, it has been…

Machine Learning · Statistics 2016-03-03 Oren Rippel , Manohar Paluri , Piotr Dollar , Lubomir Bourdev

The ratio of two densities provides a direct characterization of their differences. We consider the two-sample comparison problem by estimating this ratio given i.i.d. observations from two distributions. To this end, we propose additive…

Methodology · Statistics 2026-04-23 Naoki Awaya , Yuliang Xu , Li Ma

The composition of pretraining data is a key determinant of foundation models' performance, but there is no standard guideline for allocating a limited computational budget across different data sources. Most current approaches either rely…

Machine Learning · Computer Science 2024-10-16 Yiding Jiang , Allan Zhou , Zhili Feng , Sadhika Malladi , J. Zico Kolter

The Dollo model for reconstructing evolutionary trees from binary characters has been proposed as a generalization of the infinite sites model, also known as the Perfect Phylogeny. In particular, the Dollo model is considered more realistic…

Data Structures and Algorithms · Computer Science 2025-06-17 Paola Bonizzoni , Gianluca Della Vedova , Mauricio Soto Gomez , Gabriella Trucco

Modelling the substitution of nucleotides along a phylogenetic tree is usually done by a hidden Markov process. This allows to define a distribution of characters at the leaves of the trees and one might be able to obtain polynomial…

Populations and Evolution · Quantitative Biology 2020-10-12 Marta Casanellas , Jesús Fernández-Sánchez , Marina Garrote-López

We consider DNA codes based on the nearest-neighbor (stem) similarity model which adequately reflects the "hybridization potential" of two DNA sequences. Our aim is to present a survey of bounds on the rate of DNA codes with respect to a…

Information Theory · Computer Science 2016-11-17 A. D'yachkov , A. Voronina , A. Macula , T. Renz , V. Rykov

Many network applications are based on binary-state networks, where each component has one of two states: success or failure. Efficient algorithms to evaluate binary-state network reliability are continually being developed. Reliability…

Networking and Internet Architecture · Computer Science 2020-12-01 Wei-Chang Yeh

In this paper we introduce and study three new measures for efficient discriminative comparison of phylogenetic trees. The NNI navigation dissimilarity $d_{nav}$ counts the steps along a "combing" of the Nearest Neighbor Interchange (NNI)…

Populations and Evolution · Quantitative Biology 2015-10-21 Omur Arslan , Dan P. Guralnik , Daniel E. Koditschek

Tree structures appear in many fields of the life sciences, including phylogenetics, developmental biology and nucleic acid structures. Trees can be used to represent RNA secondary structures, which directly relate to the function of…

Machine Learning · Computer Science 2026-01-22 Pengyu Liu , Mariel Vázquez , Nataša Jonoska

Although several RDF knowledge bases are available through the LOD initiative, the ontology schema of such linked datasets is not very rich. In particular, they lack object properties. The problem of finding new object properties (and their…

Databases · Computer Science 2017-09-05 Subhashree S , P Sreenivasa Kumar

When estimating a phylogeny from a multiple sequence alignment, researchers often assume the absence of recombination. However, if recombination is present, then tree estimation and all downstream analyses will be impacted, because…

During cancer progression, malignant cells accumulate somatic mutations that can lead to genetic aberrations. In particular, evolutionary events akin to segmental duplications or deletions can alter the copy-number profile (CNP) of a set of…

Genomics · Quantitative Biology 2020-02-27 Garance Cordonnier , Manuel Lafond

As a variant of standard convolution, a dilated convolution can control effective receptive fields and handle large scale variance of objects without introducing additional computational costs. To fully explore the potential of dilated…

Computer Vision and Pattern Recognition · Computer Science 2021-05-11 Jie Liu , Chuming Li , Feng Liang , Chen Lin , Ming Sun , Junjie Yan , Wanli Ouyang , Dong Xu

Recent studies on plant disease diagnosis using machine learning (ML) have highlighted concerns about the overestimated diagnostic performance due to inappropriate data partitioning, where training and test datasets are derived from the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Yuji Arima , Satoshi Kagiwada , Hitoshi Iyatomi
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