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Multiplicative hyperrings are an important class of algebraic hyperstructures which generalize rings further to allow multiple output values for the multiplication operation. Let R be a commutative multiplicative hyperring. The 2-prime…

Commutative Algebra · Mathematics 2021-09-21 Mahdi Anbarloei

This paper describes an approximate method for global optimization of polynomial programming problems with bounded variables. The method uses a reformulation and linearization technique to transform the original polynomial optimization…

Optimization and Control · Mathematics 2012-05-30 Joseph W. Norman

In the last chapter of his book "The Algebraic Theory of Modular Systems " published in 1916, F. S. Macaulay developped specific techniques for dealing with " unmixed polynomial ideals " by introducing what he called " inverse systems ".…

Analysis of PDEs · Mathematics 2012-12-21 Jean-François Pommaret

With the exception of q-hypergeometric summation, the use of computer algebra packages implementing Zeilberger's "holonomic systems approach" in a broader mathematical sense is less common in the field of q-series and basic hypergeometric…

Symbolic Computation · Computer Science 2016-02-02 Christoph Koutschan , Peter Paule

Multivariate normal mixtures provide a flexible model for high-dimensional data. They are widely used in statistical genetics, statistical finance, and other disciplines. Due to the unboundedness of the likelihood function, classical…

Statistics Theory · Mathematics 2008-05-27 Jiahua Chen , Xianming Tan

In this talk, we discuss recent progress in the application of generalizations of polylogarithms in the symbolic computation of multi-loop integrals. We briefly review the Maple program MPL which supports a certain approach for the…

High Energy Physics - Phenomenology · Physics 2016-12-21 Christian Bogner

By double ideal quotient, we mean $(I:(I:J))$ where ideals $I$ and $J$. In our previous work [11], double ideal quotient and its variants are shown to be very useful for checking prime divisor and generating primary component. Combining…

Commutative Algebra · Mathematics 2022-02-15 Yuki Ishihara

MultiPrecisionArrays.jl is a Julia package. This package provides data structures and solvers for several variants of iterative refinement. It will become much more useful when half precision (aka Float16) is fully supported in LAPACK/BLAS.…

Numerical Analysis · Mathematics 2025-08-11 C. T. Kelley

Many applications in the sciences require numerically stable and computationally efficient evaluation of multivariate polynomials. Finding beneficial representations of polynomials, such as Horner factorisations, is therefore crucial.…

Mathematical Software · Computer Science 2020-07-30 Jannik Michelfeit

We describe the \proglang{R} package \pkg{glmmrBase} and an extension \pkg{glmmrOptim}. \pkg{glmmrBase} provides a flexible approach to specifying, fitting, and analysing generalised linear mixed models. We use an object-orientated class…

Computation · Statistics 2024-03-15 Samuel I. Watson

A primary ideal in a polynomial ring can be described by the variety it defines and a finite set of Noetherian operators, which are differential operators with polynomial coefficients. We implement both symbolic and numerical algorithms to…

Commutative Algebra · Mathematics 2023-01-25 Justin Chen , Yairon Cid-Ruiz , Marc Härkönen , Robert Krone , Anton Leykin

We offer a Maple package {\tt Poincare\_Series} for calculating the Poincar\'e series for the algebras of invariants/covariants of binary forms, for the algebras of joint invariants/covariants of several binary forms, for the kernel of…

Algebraic Geometry · Mathematics 2011-01-12 Leonid Bedratyuk

In this article we study some algebraic aspects of multicomplex numbers $\mathbb M_n$. For $n\geq 2$ a canonical representation is defined in terms of the multiplication of $n-1$ idempotent elements. This representation facilitates…

Mathematical Physics · Physics 2025-01-23 Derek Courchesne , Sébastien Tremblay

Mixture models have found uses in many areas. To list a few: unsupervised learning, empirical Bayes, latent class and trait models. The current applications of mixture models to empirical data is limited to computing a mixture model from…

Computation · Statistics 2015-09-23 Andrew Clark

This article presents some aspects and experience in the use of algebraic manipulation software applied to general relativity. Some years ago certain results were reported using computer algebra platforms, but the growing popularity of…

Computational Physics · Physics 2022-06-01 Víctor Medina

Computations over the rational numbers often encounter the problem of intermediate coefficient growth. A solution to this is provided by modular methods, which apply the algorithm under consideration modulo a number of primes and then lift…

Algebraic Geometry · Mathematics 2024-01-23 Dirk Basson , Janko Boehm , Magdaleen S. Marais , Mirko Rahn , Hobihasina P. Rakotoarisoa

Building on the recently developed theory of magnitude, we introduce the optimization algorithm EXPLO2 and carefully benchmark it. EXPLO2 advances the state of the art for optimizing high-dimensional ($D \gtrapprox 40$) multimodal functions…

Optimization and Control · Mathematics 2022-01-28 Steve Huntsman

Probabilistic programming languages and modeling toolkits are two modular ways to build and reuse stochastic models and inference procedures. Combining strengths of both, we express models and inference as generalized coroutines in the same…

Programming Languages · Computer Science 2012-05-14 Oleg Kiselyov , Chung-chieh Shan

The following article is an application of commutative algebra to the study of multiparameter persistent homology in topological data analysis. In particular, the theory of finite free resolutions of modules over polynomial rings is applied…

Representation Theory · Mathematics 2022-10-28 Amelie Schreiber

Mixed-integer linear programming (MILP) is widely employed for modeling combinatorial optimization problems. In practice, similar MILP instances with only coefficient variations are routinely solved, and machine learning (ML) algorithms are…

Optimization and Control · Mathematics 2023-03-07 Qingyu Han , Linxin Yang , Qian Chen , Xiang Zhou , Dong Zhang , Akang Wang , Ruoyu Sun , Xiaodong Luo