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A new synthesis scheme is proposed to effectively generate a random vector with prescribed joint density that induces a (latent) Gaussian tree structure. The quality of synthesis is measured by total variation distance between the…

Information Theory · Computer Science 2017-05-09 Ali Moharrer , Shuangqing Wei , George T. Amariucai , Jing Deng

This work introduces a novel nonparametric density index defined on graphs, the Sum-over-Forests (SoF) density index. It is based on a clear and intuitive idea: high-density regions in a graph are characterized by the fact that they contain…

Machine Learning · Computer Science 2013-01-07 Mathieu Senelle , Silvia Garcia-Diez , Amin Mantrach , Masashi Shimbo , Marco Saerens , François Fouss

This paper presents a brand new nonparametric density estimation strategy named the best-scored random forest density estimation whose effectiveness is supported by both solid theoretical analysis and significant experimental performance.…

Machine Learning · Statistics 2019-05-10 Hanyuan Hang , Hongwei Wen

Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiple random variables. The problem of efficient representation of probability distributions is central in term of…

Artificial Intelligence · Computer Science 2016-08-16 David Bellot , Pierre Bessiere

Unitary transformations and density matrices are central objects in quantum physics and various tasks require to introduce them in a parameterized form. In the present article we present a parameterization of the unitary group…

Quantum Physics · Physics 2010-08-18 Christoph Spengler , Marcus Huber , Beatrix C. Hiesmayr

We consider locally o-minimal structures possessing tame topological properties shared by models of DCTC and uniformly locally o-minimal expansions of the second kind of densely linearly ordered abelian groups. We derive basic properties of…

Logic · Mathematics 2023-02-22 Masato Fujita

In this article we discuss density of products of biharmonic functions vanishing on an arbitrarily small part of the boundary. We prove that one can use three or more such biharmonic functions to construct a dense subset of smooth symmetric…

Analysis of PDEs · Mathematics 2025-01-22 Divyansh Agrawal , Sombuddha Bhattacharyya , Pranav Kumar

There are several common ways to encode a tree as a matrix, such as the adjacency matrix, the Laplacian matrix (that is, the infinitesimal generator of the natural random walk), and the matrix of pairwise distances between leaves. Such…

Populations and Evolution · Quantitative Biology 2007-05-23 Frederick A. Matsen , Steven N. Evans

We present a systematic investigation into how tree-decompositions of finite adhesion capture topological properties of the space formed by a graph together with its ends. As main results, we characterise when the ends of a graph can be…

Combinatorics · Mathematics 2023-05-17 Marcel Koloschin , Thilo Krill , Max Pitz

In this work we define a metric structure to compare functions defined on different merge trees. The metric introduced possesses some stability properties, which we illustrate within a standard topological data analysis (TDA) framework, and…

Combinatorics · Mathematics 2025-07-25 Matteo Pegoraro

A {\em tree cover} of a metric space $(X,d)$ is a collection of trees, so that every pair $x,y\in X$ has a low distortion path in one of the trees. If it has the stronger property that every point $x\in X$ has a single tree with low…

Data Structures and Algorithms · Computer Science 2019-05-21 Yair Bartal , Nova Fandina , Ofer Neiman

Minimum spanning trees and forests are powerful sparsification techniques that remove cycles from weighted graphs to minimize total edge weight while preserving node connectivity. They have applications in computer science, network science,…

Discrete Mathematics · Computer Science 2024-03-25 Jordan C Rozum , Luis M Rocha

We show that an algorithmic construction of sequences of recursive trees leads to a direct proof of the convergence of random recursive trees in an associated Doob-Martin compactification; it also gives a representation of the limit in…

Probability · Mathematics 2014-07-01 Rudolf Grübel , Igor Michailow

Image segmentation foundation models (SFMs) like Segment Anything Model (SAM) have achieved impressive zero-shot and interactive segmentation across diverse domains. However, they struggle to segment objects with certain structures,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Yixin Zhang , Nicholas Konz , Kevin Kramer , Maciej A. Mazurowski

An algorithm on weighted graphs is called universally optimal if it is optimal for every input graph, in the worst case taken over all weight assignments. Informally, this means the algorithm is competitive even with algorithms that are…

Data Structures and Algorithms · Computer Science 2026-02-19 Benjamin Aram Berendsohn

Large optimal transport problems can be approached via domain decomposition, i.e. by iteratively solving small partial problems independently and in parallel. Convergence to the global minimizers under suitable assumptions has been shown in…

Optimization and Control · Mathematics 2021-06-16 Mauro Bonafini , Ismael Medina , Bernhard Schmitzer

We propose a novel approach for studying rooted trees by using functions that we will call descent functions. We provide a construction method for rooted trees that allows to study their properties through the use of descent functions.…

Number Theory · Mathematics 2014-09-23 Marco Abrate , Stefano Barbero , Umberto Cerruti , Nadir Murru

Density-equalizing map is a shape deformation technique originally developed for cartogram creation and sociological data visualization on planar geographical maps. In recent years, there has been an increasing interest in developing…

Graphics · Computer Science 2025-11-18 Shunyu Yao , Gary P. T. Choi

Reachability analysis is a powerful tool when it comes to capturing the behaviour, thus verifying the safety, of autonomous systems. However, general-purpose methods, such as Hamilton-Jacobi approaches, suffer from the curse of…

Optimization and Control · Mathematics 2022-10-27 Alessandro Alla , Peter M. Dower , Vincent Liu

Besides serving as prediction models, classification trees are useful for finding important predictor variables and identifying interesting subgroups in the data. These functions can be compromised by weak split selection algorithms that…

Applications · Statistics 2010-11-03 Wei-Yin Loh
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