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The use of operational methods of different nature is shown to be a fairly powerful tool to study different problems regarding the theory of Legendre and Legendre-like polynomials. We show how the use of the well known integral…

Classical Analysis and ODEs · Mathematics 2020-02-17 S. Licciardi , G. Dattoli , R. M. Pidatell

We describe an implementation of a genetic algorithm on partially commutative groups and apply it to the double coset search problem on a subclass of groups. This transforms a combinatorial group theory problem to a problem of combinatorial…

Group Theory · Mathematics 2007-05-23 Matthew Craven

A problem based on the Extended Euclidean Algorithm applied to a class of polynomials with many factors is presented and believed to be hard. If so, it is a one-way function well suited for applications in digital signicatures.

Cryptography and Security · Computer Science 2008-01-16 Ephraim Feig , Vivian Feig

Boolean functions are mathematical objects with numerous applications in domains like coding theory, cryptography, and telecommunications. Finding Boolean functions with specific properties is a complex combinatorial optimization problem…

Neural and Evolutionary Computing · Computer Science 2023-02-14 Marko Djurasevic , Domagoj Jakobovic , Luca Mariot , Stjepan Picek

The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard approaches to network load balancing deliver static solutions that are insufficient for the…

Networking and Internet Architecture · Computer Science 2023-07-20 Marek Bolanowski , Alicja Gerka , Andrzej Paszkiewicz , Maria Ganzha , Marcin Paprzycki

The conjugate function method is an algorithm for numerical computation of conformal mappings for simply and doubly connected domains. In this paper the conjugate function method is generalized for multiply connected domains. The key…

Numerical Analysis · Mathematics 2017-07-06 Harri Hakula , Tri Quach , Antti Rasila

The stunning empirical successes of neural networks currently lack rigorous theoretical explanation. What form would such an explanation take, in the face of existing complexity-theoretic lower bounds? A first step might be to show that…

Machine Learning · Computer Science 2017-07-18 Le Song , Santosh Vempala , John Wilmes , Bo Xie

In machine learning, the use of an artificial neural network is the mainstream approach. Such a network consists of layers of neurons. These neurons are of the same type characterized by the two features: (1) an inner product of an input…

Neural and Evolutionary Computing · Computer Science 2017-04-28 Fenglei Fan , Wenxiang Cong , Ge Wang

Finding repeated patterns or motifs in a time series is an important unsupervised task that has still a number of open issues, starting by the definition of motif. In this paper, we revise the notion of motif support, characterizing it as…

Machine Learning · Computer Science 2016-12-06 Joan Serrà , Aleksandar Matic , Josep Luis Arcos , Alexandros Karatzoglou

Generative art is a rules-driven approach to creating artistic outputs in various mediums. For example, a fluid simulation can govern the flow of colored pixels across a digital display or a rectangle placement algorithm can yield a…

Neural and Evolutionary Computing · Computer Science 2024-07-30 Erik M. Fredericks , Denton Bobeldyk , Jared M. Moore

Genetic programming is the practice of evolving formulas using crossover and mutation of genes representing functional operations. Motivated by genetic evolution we develop and solve two combinatorial games, and we demonstrate some…

Combinatorics · Mathematics 2021-02-02 Melissa A. Huggan , Craig Tennenhouse

A frame is a generalization of a basis of a vector space to a redundant overspanning set whose vectors are linearly dependent. Frames find applications in signal processing and quantum information theory. We present a genetic algorithm that…

Computational Physics · Physics 2025-08-13 Sebastián Roca-Jerat , Juan Román-Roche

A procedure for generating non-differentiable, continuously differentiable, and twice continuously differentiable classes of test functions for multiextremal multidimensional box-constrained global optimization and a corresponding package…

Optimization and Control · Mathematics 2011-03-15 Marco Gaviano , Dmitri E. Kvasov , Daniela Lera , Yaroslav D. Sergeyev

The recent surge in research focused on generating synthetic data from large language models (LLMs), especially for scenarios with limited data availability, marks a notable shift in Generative Artificial Intelligence (AI). Their ability to…

Machine Learning · Computer Science 2024-03-08 Xu Guo , Yiqiang Chen

In the monotone integer dualization problem, we are given two sets of vectors in an integer box such that no vector in the first set is dominated by a vector in the second. The question is to check if the two sets of vectors cover the…

Discrete Mathematics · Computer Science 2024-08-14 Khaled Elbassioni

We prove the existence of gaps between all the different classes of matrix monotone functions defined on an interval, provided the interval is non trivial and different from the whole real line. We then show how matrix monotone functions…

Operator Algebras · Mathematics 2007-05-23 Frank Hansen , Guoxing Ji , Jun Tomiyama

In this paper, we present some double inequalities involving certain ratios of the Gamma function. These results are further generalizations of several previous results. The approach is based on the monotonicity properties of some functions…

Classical Analysis and ODEs · Mathematics 2015-06-25 Kwara Nantomah

The double-direction orthogonalization algorithm is applied to construct sequences of polynomials, which are orthogonal over the interval [0,1]with the weighting function 1. Functional and recurrent relations are derived for the sequences…

Numerical Analysis · Mathematics 2025-10-20 Vladimir Chelyshkov

This paper studies simple bilevel problems, where a convex upper-level function is minimized over the optimal solutions of a convex lower-level problem. We first show the fundamental difficulty of simple bilevel problems, that the…

Optimization and Control · Mathematics 2025-01-28 Huaqing Zhang , Lesi Chen , Jing Xu , Jingzhao Zhang

Multitask learning is a methodology to boost generalization performance and also reduce computational intensity and memory usage. However, learning multiple tasks simultaneously can be more difficult than learning a single task because it…

Machine Learning · Computer Science 2020-06-03 Sungjae Lee , Youngdoo Son
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