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A flip of a graph is obtained by complementing the edge relation within a set of vertices. Flips are typically used to separate vertices in a graph, by increasing the distances between them. We show that in $K_{t,t}$-free graphs, every…

We present a unification and generalization of what is known in the literature as sequentially and hierarchically semi-separable (SSS and HSS) representations for matrices. Describing rank-structured representations of (inverses of) sparse…

Numerical Analysis · Mathematics 2024-08-12 Nithin Govindarajan , Shivkumar Chandrasekaran , Patrick Dewilde

In a supercritical branching particle system, the trimmed tree consists of those particles which have descendants at all times. We develop this concept in the superprocess setting. For a class of continuous superprocesses with Feller…

Probability · Mathematics 2007-05-23 Klaus Fleischmann , Jan M. Swart

We focus on modeling the relationship between an input feature vector and the predicted outcome of a trained decision tree using mixed-integer optimization. This can be used in many practical applications where a decision tree or tree…

Optimization and Control · Mathematics 2025-05-20 Max Biggs , Georgia Perakis

In this work, we propose trait-based merge trees a generalization of merge trees to feature level sets, targeting the analysis of tensor field or general multi-variate data. For this, we employ the notion of traits defined in attribute…

Machine Learning · Computer Science 2023-08-21 Jochen Jankowai , Talha Bin Masood , Ingrid Hotz

Ordinals can help prove termination for dependently typed programs. Brouwer trees are a particular ordinal notation that make it very easy to assign sizes to higher order data structures. They extend natural numbers with a limit…

Programming Languages · Computer Science 2023-12-13 Joseph Eremondi

Quasi-trees generalize trees in that the unique "path" between two nodes may be infinite and have any countable order type. They are used to define the rank-width of a countable graph in such a way that it is equal to the least upper-bound…

Logic in Computer Science · Computer Science 2023-06-22 Bruno Courcelle

Succinct data structures give space-efficient representations of large amounts of data without sacrificing performance. They rely one cleverly designed data representations and algorithms. We present here the formalization in Coq/SSReflect…

Programming Languages · Computer Science 2019-07-03 Reynald Affeldt , Jacques Garrigue , Xuanrui Qi , Kazunari Tanaka

Several real-world and abstract structures and systems are characterized by marked hierarchy to the point of being expressed as trees. Because the study of these entities often involves sampling (or discovering) the tree nodes in a specific…

Physics and Society · Physics 2022-04-18 Alexandre Benatti , Luciano da F. Costa

In many modern applications, including analysis of gene expression and text documents, the data are noisy, high-dimensional, and unordered--with no particular meaning to the given order of the variables. Yet, successful learning is often…

Methodology · Statistics 2008-07-25 Ann B. Lee , Boaz Nadler , Larry Wasserman

A closed-form formula is derived for the number of occurrences of matches of a multiset of patterns among all ordered (plane-planted) trees with a given number of edges. A pattern looks like a tree, with internal nodes and leaves, but also…

Discrete Mathematics · Computer Science 2020-06-30 Nachum Dershowitz

This paper introduces a new combinatorial framework for modeling the growth of binary trees through a discrete evolution process that incorporates a growing rule and an extinction rule. Building upon the theory of increasingly labeled…

Combinatorics · Mathematics 2026-03-30 Olivier Bodini , Antoine Genitrini , Khaydar Nurligareev

As a unification of increasing trees and plane trees, the weakly increasing trees labeled by a multiset was introduced by Lin-Ma-Ma-Zhou in 2021. Motived by some symmetries in plane trees proved recently by Dong, Du, Ji and Zhang, we…

Combinatorics · Mathematics 2025-02-14 Yang Li , Zhicong Lin

We propose Sparse Neural Network architectures that are based on random or structured bipartite graph topologies. Sparse architectures provide compression of the models learned and speed-ups of computations, they can also surpass their…

Machine Learning · Computer Science 2017-06-20 Alfred Bourely , John Patrick Boueri , Krzysztof Choromonski

Between the leaves and the nodes of a complete binary tree, a separate parent-child-sister hierarchy is employed independent of the parent-child-sister hierarchy used for the rest of the tree. Two different versions of such a local…

Data Structures and Algorithms · Computer Science 2014-01-31 Mevlut Bulut

Graphs drawn in the plane are ubiquitous, arising from data sets through a variety of methods ranging from GIS analysis to image classification to shape analysis. A fundamental problem in this type of data is comparison: given a set of such…

Computational Geometry · Computer Science 2022-10-20 Levent Batakci , Abigail Branson , Bryan Castillo , Candace Todd , Erin Wolf Chambers , Elizabeth Munch

Merge trees are a type of topological descriptors that record the connectivity among the sublevel sets of scalar fields. They are among the most widely used topological tools in visualization. In this paper, we are interested in sketching a…

Computational Geometry · Computer Science 2021-06-01 Mingzhe Li , Sourabh Palande , Lin Yan , Bei Wang

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

We establish a list of characterizations of bounded twin-width for hereditary, totally ordered binary structures. This has several consequences. First, it allows us to show that a (hereditary) class of matrices over a finite alphabet either…

We present a framework to define a large class of neural networks for which, by construction, training by gradient flow provably reaches arbitrarily low loss when the number of parameters grows. Distinct from the fixed-space global…

Optimization and Control · Mathematics 2025-01-13 David A. R. Robin , Kevin Scaman , Marc Lelarge