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Related papers: Digital Convexity and Combinatorics on Words

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We review some recent results in digital geometry obtained by using a combinatorics on words approach to discrete geometry. Motivated on the one hand by the well-known theory of Sturmian words which model conveniently discrete lines in the…

Computational Geometry · Computer Science 2011-08-19 Srečko Brlek

Recent work of Brlek \textit{et al.} gives a characterization of digitally convex polyominoes using combinatorics on words. From this work, we derive a combinatorial symbolic description of digitally convex polyominoes and use it to analyze…

Discrete Mathematics · Computer Science 2013-06-11 Olivier Bodini , Alice Jacquot , Philippe Duchon , Ljuben R. Mutafchiev

We exhibit combinatorial results on Christoffel words and binary balanced words that are motivated by their geometric interpretation as approximations of digital segments. We give a closed formula for counting the exact number of balanced…

Formal Languages and Automata Theory · Computer Science 2024-11-14 Alessandro De Luca , Gabriele Fici

Given a finite set $V$, a convexity $\mathscr{C}$, is a collection of subsets of $V$ that contains both the empty set and the set $V$ and is closed under intersections. The elements of $\mathscr{C}$ are called convex sets. The digital…

Combinatorics · Mathematics 2020-08-07 MacKenzie Carr , Christina M. Mynhardt , Ortrud R. Oellermann

We introduce a topological approach to words. Words are approximated by Gauss words and then studied up to natural modifications inspired by homotopy transformations of curves on the plane.

Combinatorics · Mathematics 2007-05-23 Vladimir Turaev

In data dominated systems and applications, a concept of representing words in a numerical format has gained a lot of attention. There are a few approaches used to generate such a representation. An interesting issue that should be…

Computation and Language · Computer Science 2020-12-08 Shahin Atakishiyev , Marek Z. Reformat

The problem of convex optimization is studied. Usually in convex optimization the minimization is over a d-dimensional domain. Very often the convergence rate of an optimization algorithm depends on the dimension d. The algorithms studied…

Machine Learning · Statistics 2015-11-05 Vladimir Temlyakov

Inflection graphs are highly complex networks representing relationships between inflectional forms of words in human languages. For so-called synthetic languages, such as Latin or Polish, they have particularly interesting structure due to…

Cellular Automata and Lattice Gases · Physics 2023-12-18 Henryk Fukś , Babak Farzad , Yi Cao

The twenty-first century is a data-driven era where human activities and behavior, physical phenomena, scientific discoveries, technology advancements, and almost everything that happens in the world resulting in massive generation,…

Artificial Intelligence · Computer Science 2025-02-10 Simon Zhang

Word meaning has different aspects, while the existing word representation "compresses" these aspects into a single vector, and it needs further analysis to recover the information in different dimensions. Inspired by quantum probability,…

Computation and Language · Computer Science 2020-04-09 Shen Li , Renfen Hu , Jinshan Wu

The anchor words algorithm performs provably efficient topic model inference by finding an approximate convex hull in a high-dimensional word co-occurrence space. However, the existing greedy algorithm often selects poor anchor words,…

Computation and Language · Computer Science 2017-11-21 Moontae Lee , David Mimno

There are two main approaches to the distributed representation of words: low-dimensional deep learning embeddings and high-dimensional distributional models, in which each dimension corresponds to a context word. In this paper, we combine…

Computation and Language · Computer Science 2014-02-19 Irina Sergienya , Hinrich Schütze

We introduce an equivalence relation, called cobordism, for words and study cobordism invariants of words inspired by methods of low-dimensional topology.

Combinatorics · Mathematics 2008-06-09 Vladimir Turaev

In the new era of internet systems and applications, a concept of detecting distinguished topics from huge amounts of text has gained a lot of attention. These methods use representation of text in a numerical format -- called embeddings --…

Computation and Language · Computer Science 2022-05-16 Danial Toufani-Movaghar , Mohammad-Reza Feizi-Derakhshi

In this paper, we explore applications of combinatorics on words across various domains, including data compression, error detection, cryptographic protocols, and pseudorandom number generation. The examination of the theoretical…

Combinatorics · Mathematics 2025-06-17 Duaa Abdullah , Jasmem Hamoud

Analysis of the convergence rates of modern convex optimization algorithms can be achived through binary means: analysis of emperical convergence, or analysis of theoretical convergence. These two pathways of capturing information diverge…

Machine Learning · Computer Science 2013-05-20 Patrick Hop , Xinghao Pan

The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed vector representations that capture a large number of precise syntactic and semantic word relationships. In this paper we…

Computation and Language · Computer Science 2013-10-18 Tomas Mikolov , Ilya Sutskever , Kai Chen , Greg Corrado , Jeffrey Dean

This paper proves a theorem about bounding orbits of a time dependent dynamical system. The maps that are involved are examples in convex dynamics, by which we mean the dynamics of piecewise isometries where the pieces are convex. The…

Dynamical Systems · Mathematics 2007-05-23 R. L. Adler , B. Kitchens , M. Martens , C. Pugh , M. Shub , C. Tresser

Convex hulls are fundamental objects in computational geometry. In moderate dimensions or for large numbers of vertices, computing the convex hull can be impractical due to the computational complexity of convex hull algorithms. In this…

Computational Geometry · Computer Science 2017-06-16 Robert Graham , Adam M. Oberman

A dictionary is a database of standard vectors, so that other vectors / signals are expressed as linear combinations of dictionary vectors, and the task of learning a dictionary for a given data is to find a good dictionary so that the…

Machine Learning · Computer Science 2020-07-09 Mohammed Rayyan Sheriff , Debasish Chatterjee
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