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We study approximation algorithms for the forest cover and bounded forest cover problems. A probabilistic $2+\epsilon$ approximation algorithm for the forest cover problem is given using the method of dual fitting. A deterministic algorithm…

Data Structures and Algorithms · Computer Science 2024-11-26 Daya Ram Gaur , Barun Gorain , Shaswati Patra , Rishi Ranjan Singh

When considering the number of subtrees of trees, the extremal structures which maximize this number among binary trees and trees with a given maximum degree lead to some interesting facts that correlate to other graphical indices in…

Combinatorics · Mathematics 2012-10-11 Xiu-Mei Zhang , Xiao-Dong Zhang , Daniel Gray , Hua Wang

The size of the largest common subtree (maximum agreement subtree) of two independent uniform random binary trees on $n$ leaves is known to be between orders $n^{1/8}$ and $n^{1/2}$. By a construction based on recursive splitting and…

Probability · Mathematics 2022-01-11 David J. Aldous

Dual-tree algorithms are a widely used class of branch-and-bound algorithms. Unfortunately, developing dual-tree algorithms for use with different trees and problems is often complex and burdensome. We introduce a four-part logical split:…

Data Structures and Algorithms · Computer Science 2013-04-17 Ryan R. Curtin , William B. March , Parikshit Ram , David V. Anderson , Alexander G. Gray , Charles L. Isbell

We develop a time-optimal $O(mn^2)$-time algorithm to construct the subtree prune-regraft (SPR) graph on a collection of m phylogenetic trees with n leaves. This improves on the previous bound of $O(mn^3)$. Such graphs are used to better…

Data Structures and Algorithms · Computer Science 2017-04-28 Chris Whidden , Frederick A. Matsen

Random Forests (RF) are among the state-of-the-art in many machine learning applications. With the ongoing integration of ML models into everyday life, the deployment and continuous application of models becomes more and more an important…

Machine Learning · Computer Science 2021-10-20 Sebastian Buschjäger , Katharina Morik

Maximum parsimony distance is a measure used to quantify the dissimilarity of two unrooted phylogenetic trees. It is NP-hard to compute, and very few positive algorithmic results are known due to its complex combinatorial structure. Here we…

Data Structures and Algorithms · Computer Science 2020-04-07 Mark Jones , Steven Kelk , Leen Stougie

Due to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to measure the dissimilarity of the two trees.…

Data Structures and Algorithms · Computer Science 2017-07-28 Zhi-Zhong Chen , Eita Machida , Lusheng Wang

Phylogenetic trees are leaf-labelled trees used to model the evolution of species. Here we explore the practical impact of kernelization (i.e. data reduction) on the NP-hard problem of computing the TBR distance between two unrooted binary…

Data Structures and Algorithms · Computer Science 2023-08-21 Rim van Wersch , Steven Kelk , Simone Linz , Georgios Stamoulis

We propose a novel method designed for large-scale regression problems, namely the two-stage best-scored random forest (TBRF). "Best-scored" means to select one regression tree with the best empirical performance out of a certain number of…

Machine Learning · Statistics 2019-05-10 Hanyuan Hang , Yingyi Chen , Johan A. K. Suykens

In this paper we present a novel probabilistic sampling-based motion planning algorithm called the Fast Marching Tree algorithm (FMT*). The algorithm is specifically aimed at solving complex motion planning problems in high-dimensional…

Robotics · Computer Science 2015-02-09 Lucas Janson , Edward Schmerling , Ashley Clark , Marco Pavone

We propose a procedure to build a decision tree which approximates the performance of complex machine learning models. This single approximation tree can be used to interpret and simplify the predicting pattern of random forests (RFs) and…

Methodology · Statistics 2016-10-31 Yichen Zhou , Giles Hooker

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

Determining the interaction partners among protein/domain families poses hard computational problems, in particular in the presence of paralogous proteins. Available approaches aim to identify interaction partners among protein/domain…

Populations and Evolution · Quantitative Biology 2015-01-14 Iman Hajirasouliha , Alexander Schönhuth , David Juan , Alfonso Valencia , S. Cenk Sahinalp

Decision trees, without appropriate constraints, can easily become overly complex and prone to overfit, capturing noise rather than generalizable patterns. To resolve this problem,pruning operation is a crucial part in optimizing decision…

Machine Learning · Computer Science 2025-08-11 Hasibul Karim Shanto , Umme Ayman Koana , Shadikur Rahman

A chief problem in phylogenetics and database theory is the computation of a maximum consistent tree from a set of rooted or unrooted trees. A standard input are triplets, rooted binary trees on three leaves, or quartets, unrooted binary…

Discrete Mathematics · Computer Science 2010-05-31 Leo van Iersel , Matthias Mnich

Rotation distance between rooted binary trees measures the number of simple operations it takes to transform one tree into another. There are no known polynomial-time algorithms for computing rotation distance. We give an efficient,…

Data Structures and Algorithms · Computer Science 2018-03-19 Sean Cleary , Katherine St. John

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

The random forest (RF) algorithm has become a very popular prediction method for its great flexibility and promising accuracy. In RF, it is conventional to put equal weights on all the base learners (trees) to aggregate their predictions.…

Machine Learning · Statistics 2023-05-18 Xinyu Chen , Dalei Yu , Xinyu Zhang

In this paper, we propose a new random forest algorithm that constructs the trees using a novel adaptive split-balancing method. Rather than relying on the widely-used random feature selection, we propose a permutation-based balanced…

Machine Learning · Statistics 2024-09-04 Yuqian Zhang , Weijie Ji , Jelena Bradic