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An infinite permutation is a linear order on the set N. We study the properties of infinite permutations generated by fixed points of some uniform binary morphisms, and find the formula for their complexity.

Discrete Mathematics · Computer Science 2011-08-19 Alexander Valyuzhenich

In several domains, data objects can be decomposed into sets of simpler objects. It is then natural to represent each object as the set of its components or parts. Many conventional machine learning algorithms are unable to process this…

Machine Learning · Computer Science 2020-03-03 Konstantinos Skianis , Giannis Nikolentzos , Stratis Limnios , Michalis Vazirgiannis

This work uses a simple quantum computer model to discuss the randomness of bit strings originated from integer sequences. The considered quantum computer model has three elements: a processing unit responsible for a mathematical operation,…

Quantum Physics · Physics 2015-05-05 R. V. Ramos

Any permutation has a disjoint cycle decomposition and concept generates an equivalence class on the symmetry group called the cycle-type. The main focus of this work is on permutations of restricted cycle-types, with particular emphasis on…

Combinatorics · Mathematics 2014-06-11 Tewodros Amdeberhan , Victor H. Moll

A coreset is a subset of the training set, using which a machine learning algorithm obtains performances similar to what it would deliver if trained over the whole original data. Coreset discovery is an active and open line of research as…

Machine Learning · Computer Science 2020-02-21 Pietro Barbiero , Giovanni Squillero , Alberto Tonda

A recent trend in binary code analysis promotes the use of neural solutions based on instruction embedding models. An instruction embedding model is a neural network that transforms sequences of assembly instructions into embedding vectors.…

Cryptography and Security · Computer Science 2022-08-16 Fiorella Artuso , Marco Mormando , Giuseppe A. Di Luna , Leonardo Querzoni

When digital data are transmitted over a noisy channel, it is important to have a mechanism allowing recovery against a limited number of errors. Normally, a user string of 0's and 1's, called bits, is encoded by adding a number of…

Information Theory · Computer Science 2019-08-28 Mario Blaum

Machine-learning (ML) models in polymer science typically treat a polymer as a single, perfectly defined molecular graph, even though real materials consist of stochastic ensembles of chains with distributed lengths. This mismatch between…

Machine Learning · Computer Science 2025-12-16 Khalid Ferji

Let $\pi=(\pi_1,\pi_2,\hdots,\pi_n)$ be permutation of the elements $1,2,\hdots,n. $ Positive integer $k\leq2^{n-1}$ we call index of $\pi,$ if in its binary notation as $n$-digital binary number, the 1's correspond to the ascent points. We…

Combinatorics · Mathematics 2010-09-23 Vladimir Shevelev

This letter introduces an abstract learning problem called the "set embedding": The objective is to map sets into probability distributions so as to lose less information. We relate set union and intersection operations with corresponding…

Machine Learning · Computer Science 2019-12-13 Ke Sun , Frank Nielsen

This document describes BinCodex, a common format for the output of binary population synthesis (BPS) codes agreed upon by the members of the LISA Synthetic UCB Catalogue Group. The goal of the format is to provide a common reference…

Instrumentation and Methods for Astrophysics · Physics 2024-04-23 Ruggero Valli , Luca Graziani , the LISA Synthetic UCB Catalogue Group

This article introduces a novel binary representation of the canonical genetic code based on both the structural similarities of the nucleotides, as well as the physicochemical properties of the encoded amino acids. Each of the four mRNA…

Biological Physics · Physics 2017-03-27 Louis R. Nemzer

A barcode is a finite multiset of intervals on the real line, $B = \{ (b_i, d_i)\}_{i=1}^n$. Barcodes are important objects in topological data analysis, where they serve as summaries of the persistent homology groups of a filtration. The…

Combinatorics · Mathematics 2022-09-14 Edgar Jaramillo-Rodriguez

Machine learning, and more specifically deep learning, have shown remarkable performance in sensing, communications, and inference. In this paper, we consider the application of the deep unfolding technique in the problem of signal…

Signal Processing · Electrical Eng. & Systems 2019-04-23 Shahin Khobahi , Naveed Naimipour , Mojtaba Soltanalian , Yonina C. Eldar

A permutiple is the product of a digit preserving multiplication, that is, a number which is an integer multiple of some permutation of its digits. Certain permutiple problems, particularly transposable, cyclic, and, more recently,…

Number Theory · Mathematics 2017-01-30 Benjamin V. Holt

This paper investigates data-driven segmentation using Re-Pair or Byte Pair Encoding-techniques. In contrast to previous work which has primarily been focused on subword units for machine translation, we are interested in the general…

Computation and Language · Computer Science 2019-04-04 Ariel Ekgren , Amaru Cuba Gyllensten , Magnus Sahlgren

A binary string representation of prime occurrences is a sequence of bits, where $1$ entries encode positions of prime numbers. This is a convenient representation for analysis of prime distribution, since it allows for application of a…

Number Theory · Mathematics 2018-10-04 Kajetan Młynarski

The number of inversions is a statistic on permutation groups measuring the degree to which the entries of a permutation are out of order. We provide a generalization of that statistic by introducing the statistic number of pseudoinversions…

Combinatorics · Mathematics 2019-06-26 Patrick Rabarison , Hery Randriamaro

A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems. Such a system recursively splits the set of classes into two subsets, and trains a binary classifier to distinguish…

Machine Learning · Statistics 2016-07-06 Tim Leathart , Bernhard Pfahringer , Eibe Frank

The problem of detecting and quantifying the presence of symmetries in datasets is useful for model selection, generative modeling, and data analysis, amongst others. While existing methods for hard-coding transformations in neural networks…

Machine Learning · Computer Science 2023-07-06 Alex Gabel , Victoria Klein , Riccardo Valperga , Jeroen S. W. Lamb , Kevin Webster , Rick Quax , Efstratios Gavves