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The strong tree property and ITP (also called the super tree property) are generalizations of the tree property that characterize strong compactness and supercompactness up to inaccessibility. That is, an inaccessible cardinal $\kappa$ is…

Logic · Mathematics 2023-12-19 William Adkisson

Accessibility percolation is a new type of percolation problem inspired by evolutionary biology. To each vertex of a graph a random number is assigned and a path through the graph is called accessible if all numbers along the path are in…

Statistical Mechanics · Physics 2013-04-04 Stefan Nowak , Joachim Krug

Trees or rooted trees have been generously studied in the literature. A forest is a set of trees or rooted trees. Here we give recurrence relations between the number of some kind of rooted forest with $k$ roots and that with $k+1$ roots on…

Combinatorics · Mathematics 2017-02-08 Song Guo , Victor J. W. Guo

The Learnable Tree Filter presents a remarkable approach to model structure-preserving relations for semantic segmentation. Nevertheless, the intrinsic geometric constraint forces it to focus on the regions with close spatial distance,…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Lin Song , Yanwei Li , Zhengkai Jiang , Zeming Li , Xiangyu Zhang , Hongbin Sun , Jian Sun , Nanning Zheng

Tree ensemble models like random forests and gradient boosting machines are widely used in machine learning due to their excellent predictive performance. However, a high-performance ensemble consisting of a large number of decision trees…

Machine Learning · Statistics 2024-10-28 Zebin Yang , Agus Sudjianto , Xiaoming Li , Aijun Zhang

The method of direct computation of universal (fibred) product in the category of commutative associative algebras of finite type with unity over a field is given and proven. The field of coefficients is not supposed to be algebraically…

Algebraic Geometry · Mathematics 2016-07-15 Nadezda V. Timofeeva

Random Forests and related tree-based methods are popular for supervised learning from table based data. Apart from their ease of parallelization, their classification performance is also superior. However, this performance, especially…

Machine Learning · Computer Science 2023-07-25 Tom Hanika , Johannes Hirth

Termination property of functions is an important issue in computability theory. In this paper, we show that repeated iterations of a function can induce an order amongst the elements of its domain set. Hasse diagram of the poset, thus…

Logic in Computer Science · Computer Science 2017-08-17 Abhinav Aggarwal , Padam Kumar

For a zero-relation algebra over a field $\mathcal K$, Crawley-Boevey introduced the concept of a tree module and provided a combinatorial description of a basis for the space of homomorphisms between two tree modules--the basis elements…

Representation Theory · Mathematics 2025-08-13 Annoy Sengupta , Amit Kuber

When trained on language data, do transformers learn some arbitrary computation that utilizes the full capacity of the architecture or do they learn a simpler, tree-like computation, hypothesized to underlie compositional meaning systems…

Computation and Language · Computer Science 2022-11-07 Shikhar Murty , Pratyusha Sharma , Jacob Andreas , Christopher D. Manning

In repeated games, players choose actions concurrently at each step. We consider a parameterized setting of repeated games in which the players form a population of an arbitrary size. Their utility functions encode a reachability objective.…

Computer Science and Game Theory · Computer Science 2025-10-06 Nathalie Bertrand , Patricia Bouyer , Luc Lapointe , Corto Mascle

Tree-width is an invaluable tool for computational problems on graphs. But often one would like to compute on other kinds of objects (e.g. decorated graphs or even algebraic structures) where there is no known tree-width analogue. Here we…

Combinatorics · Mathematics 2022-06-22 Benjamin Merlin Bumpus , Zoltan A. Kocsis

By measuring or calculating coalescence times for several models of coalescence or evolution, with and without selection, we show that the ratios of these coalescence times become universal in the large size limit and we identify a few…

Disordered Systems and Neural Networks · Physics 2009-11-13 Eric Brunet , Bernard Derrida , Damien Simon

A finite-dimensional unital and associative algebra over $\mathbb{R}$, or what we shall call simply "an algebra" in this paper for short, generalities the construction by which we derive the complex numbers by "adjoining an element $i$" to…

Rings and Algebras · Mathematics 2017-08-04 Nathan BeDell

Taking a Feynman categorical perspective, several key aspects of the geometry of surfaces are deduced from combinatorial constructions with graphs. This provides a direct route from combinatorics of graphs to string topology operations via…

Algebraic Topology · Mathematics 2022-01-26 Clemens Berger , Ralph M. Kaufmann

Since the early Sixties and Seventies it has been known that the regular and context-free languages are characterized by definability in the monadic second-order theory of certain structures. More recently, these descriptive…

cmp-lg · Computer Science 2016-08-31 James Rogers

We study a categorical generalisation of tree automata, as $\Sigma$-algebras for a fixed endofunctor $\Sigma$ endowed with initial and final states. Under mild assumptions about the base category, we present a general minimisation algorithm…

Formal Languages and Automata Theory · Computer Science 2023-02-03 Gerco van Heerdt , Tobias Kappé , Jurriaan Rot , Matteo Sammartino , Alexandra Silva

This paper deals with graph automaton groups associated with trees and some generalizations. We start by showing some algebraic properties of tree automaton groups. Then we characterize the associated semigroup, proving that it is…

Group Theory · Mathematics 2023-04-10 Matteo Cavaleri , Daniele D'Angeli , Alfredo Donno , Emanuele Rodaro

The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has rapidly grown in an attempt to better control and fix…

Machine Learning · Computer Science 2021-02-02 Thibaut Vidal , Toni Pacheco , Maximilian Schiffer

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos