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A binary tanglegram is a pair <S,T> of 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 or software engineering, it is required…

Data Structures and Algorithms · Computer Science 2009-05-15 Martin Nöllenburg , Danny Holten , Markus Völker , Alexander Wolff

This paper presents a novel approach to automatically solving arithmetic word problems. This is the first algorithmic approach that can handle arithmetic problems with multiple steps and operations, without depending on additional…

Computation and Language · Computer Science 2016-08-23 Subhro Roy , Dan Roth

Binary trees are fundamental objects in models of evolutionary biology and population genetics. Here, we discuss some of their combinatorial and structural properties as they depend on the tree class considered. Furthermore, the process by…

Populations and Evolution · Quantitative Biology 2021-06-30 Thomas Wiehe

The purpose of this paper is to analyze certain statistics of a recently introduced non-uniform random tree model, biased recursive trees. This model is based on constructing a random tree by establishing a correspondence with non-uniform…

Probability · Mathematics 2018-01-16 Ella Hiesmayr , Ümit Işlak

Clustering serves as a vital tool for uncovering latent data structures, and achieving both high accuracy and interpretability is essential. To this end, existing methods typically construct binary decision trees by solving mixed-integer…

Machine Learning · Computer Science 2026-02-17 Hayato Suzuki , Shunnosuke Ikeda , Yuichi Takano

A central limit theorem for binary tree is numerically examined. Two types of central limit theorem for higher-order branches are formulated. A topological structure of a binary tree is expressed by a binary sequence, and the…

Data Analysis, Statistics and Probability · Physics 2013-04-10 Ken Yamamoto , Yoshihiro Yamazaki

Meta-analysis represents a widely accepted approach for evaluating the accuracy of diagnostic tools in clinical and psychological investigations. This paper investigates the applicability of multinomial tree models recently suggested in the…

Methodology · Statistics 2024-05-29 Annamaria Guolo

The Steiner tree enumeration problem is a well known problem that asks for enumerating Steiner trees. Numerous theoretical works proposed algorithms for the problem and analyzed their complexity, but there are no practical algorithms and…

Data Structures and Algorithms · Computer Science 2021-04-20 Yuya Sasaki

In this paper, based on results of exact learning and test theory, we study arbitrary infinite binary information systems each of which consists of an infinite set of elements and an infinite set of two-valued functions (attributes) defined…

Computational Complexity · Computer Science 2022-01-13 Mikhail Moshkov

In this paper, we propose an explicit, non-strict representation of search trees in constraint-logic object-oriented programming. Our search tree representation includes both the non-deterministic and deterministic behaviour during…

Programming Languages · Computer Science 2020-09-23 Jan C. Dageförde , Finn Teegen

Purpose: This paper presents an algorithm that can elicitate (infer) all or any combination of ELECTRE Tri-B parameters. For example, a decision-maker can maintain the values for indifference, preference, and veto thresholds, and our…

Machine Learning · Computer Science 2021-04-12 Gabriela Montenegro de Barros , Valdecy Pereira

Decision trees and random forest remain highly competitive for classification on medium-sized, standard datasets due to their robustness, minimal preprocessing requirements, and interpretability. However, a single tree suffers from high…

Machine Learning · Statistics 2025-12-02 Cencheng Shen , Yuexiao Dong , Carey E. Priebe

We study compact straight-line embeddings of trees. We show that perfect binary trees can be embedded optimally: a tree with $n$ nodes can be drawn on a $\sqrt n$ by $\sqrt n$ grid. We also show that testing whether a given binary tree has…

Computational Geometry · Computer Science 2018-09-03 Hugo A. Akitaya , Maarten Löffler , Irene Parada

The main goal of this paper is to describe a new pruning method for solving decision trees and game trees. The pruning method for decision trees suggests a slight variant of decision trees that we call scenario trees. In scenario trees, we…

Artificial Intelligence · Computer Science 2013-02-21 Prakash P. Shenoy

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

There are many approaches for training decision trees. This work introduces a novel gradient-based method for constructing decision trees that optimize arbitrary differentiable loss functions, overcoming the limitations of heuristic…

Machine Learning · Computer Science 2025-03-25 Andrei V. Konstantinov , Lev V. Utkin

Tree rotations (left and right) are basic local deformations allowing to transform between two unlabeled binary trees of the same size. Hence, there is a natural problem of practically finding such transformation path with low number of…

Data Structures and Algorithms · Computer Science 2016-10-20 Jarek Duda

In this paper, we address the scenario where nodes with sensor data are connected in a tree network, and every node wants to compute a given symmetric Boolean function of the sensor data. We first consider the problem of computing a…

Information Theory · Computer Science 2010-05-03 Hemant Kowshik , P. R. Kumar

We describe a combinatorial approach for investigating properties of rational numbers. The overall approach rests on structural bijections between rational numbers and familiar combinatorial objects, namely rooted trees. We emphasize that…

Combinatorics · Mathematics 2012-01-13 Edinah K. Gnang , Chetan Tonde

We propose a model-based clustering algorithm for a general class of functional data for which the components could be curves or images. The random functional data realizations could be measured with error at discrete, and possibly random,…

Machine Learning · Statistics 2022-03-14 Steven Golovkine , Nicolas Klutchnikoff , Valentin Patilea
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