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In this study, we investigate whether speech symbols, learned through deep learning, follow Zipf's law, akin to natural language symbols. Zipf's law is an empirical law that delineates the frequency distribution of words, forming…

Computation and Language · Computer Science 2023-09-19 Shinnosuke Takamichi , Hiroki Maeda , Joonyong Park , Daisuke Saito , Hiroshi Saruwatari

Tree-child networks are a recently-described class of directed acyclic graphs that have risen to prominence in phylogenetics (the study of evolutionary trees and networks). Although these networks have a number of attractive mathematical…

Probability · Mathematics 2023-01-10 François Bienvenu , Amaury Lambert , Mike Steel

We provide an efficient encoding of the natural numbers {0,1,2,3,...} as strings of nested parentheses {(),(()),(()()),((())),...}, or considered inversely, an efficient enumeration of such strings. The technique is based on the recursive…

Discrete Mathematics · Computer Science 2012-11-16 R. D. Ogden

The frequencies at which individual words occur across languages follow power law distributions, a pattern of findings known as Zipf's law. A vast literature argues over whether this serves to optimize the efficiency of human communication,…

Computation and Language · Computer Science 2020-01-16 Michael Ramscar

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

The relative importance of the intrinsic and extrinsic factors determining the variety of geometric shapes exhibited by dendritic trees remains unclear. This question was addressed by developing a model of the growth of dendritic trees…

Neurons and Cognition · Quantitative Biology 2007-05-23 Artur Luczak

We establish limit theorems that describe the asymptotic local and global geometric behaviour of random enriched trees considered up to symmetry. We apply these general results to random unlabelled weighted rooted graphs and uniform random…

Probability · Mathematics 2016-12-15 Benedikt Stufler

Directed covers of finite graphs are also known as periodic trees or trees with finitely many cone types. We expand the existing theory of directed covers of finite graphs to those of infinite graphs. While the lower growth rate still…

Probability · Mathematics 2009-10-05 Lorenz A. Gilch , Sebastian Müller

Dynamic trees are mixtures of tree structured belief networks. They solve some of the problems of fixed tree networks at the cost of making exact inference intractable. For this reason approximate methods such as sampling or mean field…

Machine Learning · Computer Science 2013-01-18 Amos J. Storkey

In biology, a phylogenetic tree is a tool to represent the evolutionary relationship between species. Unfortunately, the classical Schr\"oder tree model is not adapted to take into account the chronology between the branching nodes. In…

Data Structures and Algorithms · Computer Science 2019-01-15 Olivier Bodini , Antoine Genitrini , Mehdi Naima

The dependence with text length of the statistical properties of word occurrences has long been considered a severe limitation quantitative linguistics. We propose a simple scaling form for the distribution of absolute word frequencies…

Physics and Society · Physics 2015-06-15 Francesc Font-Clos , Gemma Boleda , Álvaro Corral

We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected…

Statistical Mechanics · Physics 2014-12-25 Z. Kalay , E. Ben-Naim

Easy-first parsing relies on subtree re-ranking to build the complete parse tree. Whereas the intermediate state of parsing processing is represented by various subtrees, whose internal structural information is the key lead for later…

Computation and Language · Computer Science 2019-06-12 Zuchao Li , Jiaxun Cai , Hai Zhao

In invasion percolation, the edges of successively maximal weight (the outlets) divide the invasion cluster into a chain of ponds separated by outlets. On the regular tree, the ponds are shown to grow exponentially, with law of large…

Probability · Mathematics 2012-07-24 Jesse Goodman

Datasets from several domains, such as life-sciences, semantic web, machine learning, natural language processing, etc. are naturally structured as acyclic graphs. These datasets, particularly those in bio-informatics and computational…

Discrete Mathematics · Computer Science 2014-09-02 Sandeep Gupta

We show that the growth of a unimodular random rooted tree $(T,o)$ of degree bounded by $d$ always exists, assuming its upper growth passes the critical threshold $\sqrt{d-1}$. This complements Timar's work who showed the possible…

Probability · Mathematics 2023-12-11 Miklós Abert , Mikołaj Frączyk , Ben Hayes

Every encoding has priori information if the encoding represents any semantic information of the unverse or object. Encoding means mapping from the unverse to the string or strings of digits. The semantic here is used in the model-theoretic…

Artificial Intelligence · Computer Science 2009-03-24 Xiuli Wang

Routing tables in ad hoc and wireless routing protocols can be represented using rooted trees. The constant need for communication and storage of these trees in routing protocols demands an efficient rooted tree coding algorithm. This…

Networking and Internet Architecture · Computer Science 2022-07-13 Amirmohammad Farzaneh , Mihai-Alin Badiu , Justin P. Coon

The modular decomposition of a symmetric map $\delta\colon X\times X \to \Upsilon$ (or, equivalently, a set of symmetric binary relations, a 2-structure, or an edge-colored undirected graph) is a natural construction to capture key features…

Combinatorics · Mathematics 2021-03-12 Carmen Bruckmann , Peter F. Stadler , Marc Hellmuth

This work presents a novel means for understanding learning dynamics and scaling relations in neural networks. We show that certain measures on the spectrum of the empirical neural tangent kernel, specifically entropy and trace, yield…

Machine Learning · Computer Science 2024-10-11 Samuel Tovey , Sven Krippendorf , Michael Spannowsky , Konstantin Nikolaou , Christian Holm