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Each gene has its own evolutionary history which can substantially differ from the evolutionary histories of other genes. For example, some individual genes or operons can be affected by specific horizontal gene transfer and recombination…

Populations and Evolution · Quantitative Biology 2022-05-26 Nadia Tahiri , Bernard Fichet , Vladimir Makarenkov

Scalable high-quality MAP inference in arbitrary-order Markov Random Fields (MRFs) remains challenging. Approximate message-passing methods are often efficient but can degrade on dense or high-order instances, while exact solvers such as…

Machine Learning · Computer Science 2026-05-08 Yaomin Wang , Chaolong Ying , Xiaodong Luo , Tianshu Yu

Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of…

Populations and Evolution · Quantitative Biology 2015-07-20 Frederick A Matsen , Sara Billey , Arnold Kas , Matjaž Konvalinka

Within the field of phylogenetics there is great interest in distance measures to quantify the dissimilarity of two trees. Recently, a new distance measure has been proposed: the Maximum Parsimony (MP) distance. This is based on the…

Populations and Evolution · Quantitative Biology 2015-01-20 Steven Kelk , Mareike Fischer

We introduce Tree-AMP, standing for Tree Approximate Message Passing, a python package for compositional inference in high-dimensional tree-structured models. The package provides a unifying framework to study several approximate message…

Machine Learning · Statistics 2023-04-19 Antoine Baker , Benjamin Aubin , Florent Krzakala , Lenka Zdeborová

Random Forests (RF) and Extreme Gradient Boosting (XGBoost) are two of the most widely used and highly performing classification and regression models. They aggregate equally weighted CART trees, generated randomly in RF or sequentially in…

Machine Learning · Computer Science 2025-10-28 Dimitris Bertsimas , Yubing Cui

It has remained an open question for some time whether, given a set of not necessarily binary (i.e. "nonbinary") trees T on a set of taxa X, it is possible to determine in time f(r).poly(m) whether there exists a phylogenetic network that…

Populations and Evolution · Quantitative Biology 2012-08-03 Steven Kelk , Celine Scornavacca

The problem of reconstructing evolutionary trees or phylogenies is of great interest in computational biology. A popular model for this problem assumes that we are given the set of leaves (current species) of an unknown binary tree and the…

Data Structures and Algorithms · Computer Science 2022-06-16 Eshwar Ram Arunachaleswaran , Anindya De , Sampath Kannan

Within the field of phylogenetics there is great interest in distance measures to quantify the dissimilarity of two trees. Here, based on an idea of Bruen and Bryant, we propose and analyze a new distance measure: the Maximum Parsimony (MP)…

Populations and Evolution · Quantitative Biology 2014-02-10 Mareike Fischer , Steven Kelk

In the $L_0$ Fitting Tree Metrics problem, we are given all pairwise distances among the elements of a set $V$ and our output is a tree metric on $V$. The goal is to minimize the number of pairwise distance disagreements between the input…

Data Structures and Algorithms · Computer Science 2023-08-01 Evangelos Kipouridis

Markov random fields (MRFs) are a powerful tool for modelling statistical dependencies for a set of random variables using a graphical representation. An important computational problem related to MRFs, called maximum a posteriori (MAP)…

Data Structures and Algorithms · Computer Science 2017-08-11 Alexander Bauer , Shinichi Nakajima , Nico Görnitz , Klaus-Robert Müller

We consider T-optimal experiment design problems for discriminating multi-factor polynomial regression models where the design space is defined by polynomial inequalities and the regression parameters are constrained to given convex sets.…

Computation · Statistics 2020-02-04 Yuguang Yue , Lieven Vandenberghe , Weng Kee Wong

Introduced by Breiman, Random Forests are widely used classification and regression algorithms. While being initially designed as batch algorithms, several variants have been proposed to handle online learning. One particular instance of…

Machine Learning · Statistics 2019-04-10 Jaouad Mourtada , Stéphane Gaïffas , Erwan Scornet

A \emph{binary tanglegram} is a drawing of a pair of rooted binary trees whose leaf sets are in one-to-one correspondence; matching leaves are connected by inter-tree edges. For applications, for example, in phylogenetics, it is essential…

Computational Geometry · Computer Science 2010-09-17 Kevin Buchin , Maike Buchin , Jaroslaw Byrka , Martin Nöllenburg , Yoshio Okamoto , Rodrigo I. Silveira , Alexander Wolff

Maximum parsimony is one of the most frequently-discussed tree reconstruction methods in phylogenetic estimation. However, in recent years it has become more and more apparent that phylogenetic trees are often not sufficient to describe…

Populations and Evolution · Quantitative Biology 2016-10-25 Christopher Bryant , Mareike Fischer , Simone Linz , Charles Semple

Evolutionary histories for species that cross with one another or exchange genetic material can be represented by leaf-labelled, directed graphs called phylogenetic networks. A major challenge in the burgeoning area of phylogenetic networks…

Data Structures and Algorithms · Computer Science 2021-09-24 Leo van Iersel , Sjors Kole , Vincent Moulton , Leonie Nipius

It is an open question whether there exists a polynomial-time algorithm for computing the rotation distances between pairs of extended ordered binary trees. The problem of computing the rotation distance between an arbitrary pair of trees,…

Data Structures and Algorithms · Computer Science 2020-01-20 Sean Cleary , Roland Maio

Axis-aligned decision trees are fast and stable but struggle on datasets with rotated or interaction-dependent decision boundaries, where informative splits require linear combinations of features rather than single-feature thresholds.…

Machine Learning · Computer Science 2025-12-10 Sarwesh Rauniyar

Random forests are widely used in regression. However, the decision trees used as base learners are poor approximators of linear relationships. To address this limitation we propose RaFFLE (Random Forest Featuring Linear Extensions), a…

Machine Learning · Computer Science 2025-02-17 Jakob Raymaekers , Peter J. Rousseeuw , Thomas Servotte , Tim Verdonck , Ruicong Yao

Genomics has revolutionized biology, enabling the interrogation of whole transcriptomes, genome-wide binding sites for proteins, and many other molecular processes. However, individual genomic assays measure elements that interact in vivo…

Machine Learning · Statistics 2022-06-08 Sumanta Basu , Karl Kumbier , James B. Brown , Bin Yu