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Related papers: Selection and Coalescence in a Finite State Model

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We consider a random process on recursive trees, with three types of events. Vertices give birth at a constant rate (growth), each edge may be removed independently (fragmentation of the tree) and clusters (or trees) are frozen with a rate…

Probability · Mathematics 2022-09-07 Vincent Bansaye , Chenlin Gu , Linglong Yuan

We initiate a study of a query-driven approach to designing partition trees for range-searching problems. Our model assumes that a data structure is to be built for an unknown query distribution that we can access through a sampling oracle,…

Data Structures and Algorithms · Computer Science 2025-02-20 Dimitris Fotakis , Andreas Kalavas , Ioannis Psarros

Algorithms for binary classification based on adaptive tree partitioning are formulated and analyzed for both their risk performance and their friendliness to numerical implementation. The algorithms can be viewed as generating a set…

Statistics Theory · Mathematics 2014-11-05 Peter Binev , Albert Cohen , Wolfgang Dahmen , Ronald DeVore

Phylogenetic trees are widely used to understand the evolutionary history of organisms. Tree shapes provide information about macroevolutionary processes. However, macroevolutionary models are unreliable for inferring the true processes…

Populations and Evolution · Quantitative Biology 2021-10-11 Albert Ch. Soewongsono , Barbara R. Holland , Małgorzata M. O'Reilly

We propose a tree regularization framework, which enables many tree models to perform feature selection efficiently. The key idea of the regularization framework is to penalize selecting a new feature for splitting when its gain (e.g.…

Machine Learning · Computer Science 2012-03-22 Houtao Deng , George Runger

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds, that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their…

Numerical Analysis · Mathematics 2020-12-02 Miranda Holmes-Cerfon

We explore the effect of finite population sampling in design problems with many variables cross-classified in many ways. In particular, we investigate designs where we wish to sample individuals belonging to different groups for which the…

Methodology · Statistics 2017-11-30 Simon C. Shaw , Michael Goldstein

We are interested in modelling Darwinian evolution, resulting from the interplay of phenotypic variation and natural selection through ecological interactions. Our models are rooted in the microscopic, stochastic description of a population…

Probability · Mathematics 2016-08-16 Nicolas Champagnat , Régis Ferrière , Sylvie Méléard

Co-clustering, that is, partitioning a numerical matrix into homogeneous submatrices, has many applications ranging from bioinformatics to election analysis. Many interesting variants of co-clustering are NP-hard. We focus on the basic…

Discrete Mathematics · Computer Science 2019-06-17 Laurent Bulteau , Vincent Froese , Sepp Hartung , Rolf Niedermeier

W. D. Hamilton's celebrated formula for the age-specific force of natural selection furnishes predictions for senescent mortality due to mutation accumulation, at the price of reliance on a linear approximation. Applying to Hamilton's…

Populations and Evolution · Quantitative Biology 2008-07-04 Kenneth W. Wachter , Steven N. Evans , David R. Steinsaltz

We define a doubly infinite, monotone labeling of Bienayme-Galton-Watson (BGW) genealogies. The genealogy of the current generation backwards in time is uniquely determined by the coalescent point process $(A_i; i\ge 1)$, where $A_i$ is the…

Probability · Mathematics 2015-03-17 Amaury Lambert , Lea Popovic

The varying-coefficient model is a strong tool for the modelling of interactions in generalized regression. It is easy to apply if both the variables that are modified as well as the effect modifiers are known. However, in general one has a…

Methodology · Statistics 2017-05-25 Moritz Berger , Gerhard Tutz , Matthias Schmid

Partitioning large machine learning models across distributed accelerator systems is a complex process, requiring a series of interdependent decisions that are further complicated by internal sharding ambiguities. Consequently, existing…

This paper presents two case studies of data sets where the main inferential goal is to characterize time-varying patterns in model structure. Both of these examples are seen to be general cases of the so-called "partition problem," where…

Applications · Statistics 2011-11-03 Zesong Liu , Jesse Windle , James G. Scott

A density-dependent branching process is a particle system in which individuals reproduce independently, but in a way that depends on the current population size. This feature can model a wide range of ecological interactions at the cost of…

Probability · Mathematics 2026-01-23 Mathilde André , Félix Foutel-Rodier , Emmanuel Schertzer

Recursive decision trees are widely used to estimate heterogeneous causal treatment effects in experimental and observational studies. These methods are typically implemented using CART-type recursive partitioning and are often viewed as…

Statistics Theory · Mathematics 2026-03-19 Matias D. Cattaneo , Jason M. Klusowski , Ruiqi Rae Yu

We investigate a simple quantitative genetics model subjet to a gradual environmental change from the viewpoint of the phylogenies of the living individuals. We aim to understand better how the past traits of their ancestors are shaped by…

Probability · Mathematics 2021-04-22 Vincent Calvez , Benoît Henry , Sylvie Méléard , Viet Chi Tran

Inference of the evolutionary histories of species, commonly represented by a species tree, is complicated by the divergent evolutionary history of different parts of the genome. Different loci on the genome can have different histories…

Populations and Evolution · Quantitative Biology 2020-10-14 Andrew Richards , Laura Kubatko

This paper is concerned with the selection and estimation of fixed and random effects in linear mixed effects models. We propose a class of nonconcave penalized profile likelihood methods for selecting and estimating important fixed…

Statistics Theory · Mathematics 2012-11-05 Yingying Fan , Runze Li

This paper proposes a stochastic block model with dynamics where the population grows using preferential attachment. Nodes with higher weighted degree are more likely to recruit new nodes, and nodes always recruit nodes from their own…

Social and Information Networks · Computer Science 2024-01-15 Simina Brânzei , Nithish Kumar , Gireeja Ranade
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