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An operatorial method, already employed to formulate a generalization of the Ramanujan master theorem, is applied to the evaluation of integrals of various type. This technique provide a very flexible and powerful tool yielding new results…

Classical Analysis and ODEs · Mathematics 2012-11-07 D. Babusci , G. Dattoli , G. H. E. Duchamp , K. Górska , K. A. Penson

Clustering algorithms rely on complex optimisation processes that may be difficult to comprehend, especially for individuals who lack technical expertise. While many explainable artificial intelligence techniques exist for supervised…

Machine Learning · Computer Science 2024-09-20 Aurora Spagnol , Kacper Sokol , Pietro Barbiero , Marc Langheinrich , Martin Gjoreski

Could elementary complex analysis, which covers the topics such as algebra of complex numbers, elementary complex functions, complex differentiation and integration, series expansions of complex functions, residues and singularities, and…

Complex Variables · Mathematics 2016-10-27 Agamirza E. Bashirov , Sajedeh Norozpour

Diffusive representations of fractional derivatives have proven to be useful tools in the construction of fast and memory efficient numerical methods for solving fractional differential equations. A common challenge in many of the known…

Numerical Analysis · Mathematics 2022-04-11 Kai Diethelm

Mathematical programming is a branch of applied mathematics and has recently been used to derive new decoding approaches, challenging established but often heuristic algorithms based on iterative message passing. Concepts from mathematical…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Stefan Ruzika , Akin Tanatmis

Derivatives play a critical role in computational statistics, examples being Bayesian inference using Hamiltonian Monte Carlo sampling and the training of neural networks. Automatic differentiation is a powerful tool to automate the…

Mathematical Software · Computer Science 2019-03-27 Charles C. Margossian

We give an algorithm to compute inhomogeneous differential equations for definite integrals with parameters. The algorithm is based on the integration algorithm for $D$-modules by Oaku. Main tool in the algorithm is the Gr\"obner basis…

Algebraic Geometry · Mathematics 2010-07-15 Hiromasa Nakayama , Kenta Nishiyama

This paper presents a novel set-based computing method, called interval superposition arithmetic, for enclosing the image set of multivariate factorable functions on a given domain. In order to construct such enclosures, the proposed…

Numerical Analysis · Mathematics 2018-02-14 Yanlin Zha , Mario E. Villanueva , Boris Houska

In this paper, we propose a new method for removing all the redundant inequalities generated by Fourier-Motzkin elimination. This method is based on an improved version of Balas' work and can also be used to remove all the redundant…

Symbolic Computation · Computer Science 2019-05-14 Rui-Juan Jing , Marc Moreno-Maza , Delaram Talaashrafi

The pseudoinverse of a matrix, a generalized notion of the inverse, is of fundamental importance in linear algebra and, thereby, in many different fields. Despite its proven existence, an algorithmic approach is typically necessary to…

Numerical Analysis · Mathematics 2026-01-21 Holger Boche , Adalbert Fono , Gitta Kutyniok

In this paper, we propose a new scheme for the integration of the periodic nonlinear Schr\"{o}dinger equation and rigorously prove convergence rates at low regularity. The new integrator has decisive advantages over standard schemes at low…

Analysis of PDEs · Mathematics 2020-12-01 Alexander Ostermann , Frédéric Rousset , Katharina Schratz

We study the integration of functions with respect to an unknown density. We compare the simple Monte Carlo method (which is almost optimal for a certain large class of inputs) and compare it with the Metropolis algorithm (based on a…

Numerical Analysis · Mathematics 2007-06-13 Peter Mathe , Erich Novak

There are many methods for finding a particular solution to a nonhomogeneous linear ordinary differential equation (ODE) with constant coefficients. The method of undetermined coefficients, Laplace transform method and differential operator…

General Mathematics · Mathematics 2021-03-08 Jozef Fecenko

In many classification problems it is desirable to output well-calibrated probabilities on the different classes. We propose a robust, non-parametric method of calibrating probabilities called SplineCalib that utilizes smoothing splines to…

Machine Learning · Statistics 2018-09-21 Brian Lucena

Fourier Series is the second of monographs we present on harmonic analysis. Harmonic analysis is one of the most fascinating areas of research in mathematics. Its centrality in the development of many areas of mathematics such as partial…

History and Overview · Mathematics 2022-06-13 Kecheng Zhou , M. Vali Siadat

The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML applications have been developed, such as datamining programs,…

Artificial Intelligence · Computer Science 2007-05-23 Sergio Alejandro Gomez , Carlos Ivan Chesñevar

Suppose that a mobile sensor describes a Markovian trajectory in the ambient space. At each time the sensor measures an attribute of interest, e.g., the temperature. Using only the location history of the sensor and the associated…

Statistics Theory · Mathematics 2017-10-02 Romain Azaïs , Bernard Delyon , François Portier

A new general and unified method of summation, which is both regular and consistent, is invented. It is based on the idea concerning a way of integers reordering. The resulting theory includes a number of explicit and closed form summation…

Classical Analysis and ODEs · Mathematics 2011-10-26 Armen Bagdasaryan

We present a conspicuous number of indefinite integrals involving Heun functions and their products obtained by means of the Lagrangian formulation of a general homogeneous linear ordinary differential equation. As a by-product we also…

Classical Analysis and ODEs · Mathematics 2018-07-24 Davide Batic , Omar Forrest , Marek Nowakowski

We propose a supervised learning algorithm for machine learning applications. Contrary to the model developing in the classical methods, which treat training, validation, and test as separate steps, in the presented approach, there is a…

Machine Learning · Computer Science 2019-09-24 Soheil Mehrabkhani
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