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We present upper bounds on the bit-size of coefficients of non-radical lexicographical Groebner bases in purely triangular form (triangular sets) of dimension zero. This extends a previous work [Dahan-Schost, Issac'2004], constrained to…

Symbolic Computation · Computer Science 2017-10-18 Xavier Dahan

In this work, it is proposed a method for computing Noncommutative Gr\"obner bases over a valuation n{\oe}therian ring. We have generalized the fundamental theorem on normal forms over an arbitrary ring. The classical method of dynamical…

Rings and Algebras · Mathematics 2012-08-14 André Mialebama Bouesso , Djiby Sow

Recent research has shown that alignment between the structure of graph data and the geometry of an embedding space is crucial for learning high-quality representations of the data. The uniform geometry of Euclidean and hyperbolic spaces…

Machine Learning · Computer Science 2023-06-27 Wei Zhao , Federico Lopez , J. Maxwell Riestenberg , Michael Strube , Diaaeldin Taha , Steve Trettel

In geostatistics, traditional spatial models often rely on the Gaussian Process (GP) to fit stationary covariances to data. It is well known that this approach becomes computationally infeasible when dealing with large data volumes,…

Computation · Statistics 2024-09-17 Antony Sikorski , Daniel McKenzie , Douglas Nychka

We give a new complexity bound for calculating the complex dimension of an algebraic set. Our algorithm is completely deterministic and approaches the best recent randomized complexity bounds. We also present some new, significantly sharper…

Algebraic Geometry · Mathematics 2025-10-20 J. Maurice Rojas

We consider the problem of determining Gr\"obner bases of binomial ideals associated with linear error correcting codes. Computation of Gr\"obner bases of linear codes have become a topic of interest to many researchers in coding theory…

Information Theory · Computer Science 2017-07-25 Arunkumar R. Patil , Nitin S. Darkunde

This work addresses the problem of simulating Gaussian random fields that are continuously indexed over a class of metric graphs, termed graphs with Euclidean edges, being more general and flexible than linear networks. We introduce three…

Statistics Theory · Mathematics 2024-04-29 Alfredo Alegría , Xavier Emery , Tobia Filosi , Emilio Porcu

In recent years tamed schemes have become an important technique for simulating SDEs and SPDEs whose continuous coefficients display superlinear growth. The taming method, which involves curbing the growth of the coefficients as a function…

Probability · Mathematics 2022-11-23 Tim Johnston , Sotirios Sabanis

Gr\"obner bases have been generalized by replacing monomial orders with constructions such as valuations and filtrations. We consider suitable valuations on a rational valuation field $K(x,y)$ and analyze their behavior when restricting to…

Commutative Algebra · Mathematics 2018-06-01 Edward Mosteig

We present foundational work on standard bases over rings and on Boolean Groebner bases in the framework of Boolean functions. The research was motivated by our collaboration with electrical engineers and computer scientists on problems…

Commutative Algebra · Mathematics 2008-02-04 Michael Brickenstein , Alexander Dreyer , Gert-Martin Greuel , Markus Wedler , Oliver Wienand

It is known that for binary codes one can use Gr\"obner bases to obtain a subset of codewords of minimal support that can be used to determine the second generalized Hamming weight of the code. In this paper we establish conditions on a…

Commutative Algebra · Mathematics 2025-10-14 Hernán de Alba , Cecilia Martínez-Reyes

We develop subgradient- and gradient-based methods for minimizing strongly convex functions under a notion which generalizes the standard Euclidean strong convexity. We propose a unifying framework for subgradient methods which yields two…

Optimization and Control · Mathematics 2016-08-19 Masaru Ito

A dominant approach for addressing unsupervised domain adaptation is to map data points for the source and the target domains into an embedding space which is modeled as the output-space of a shared deep encoder. The encoder is trained to…

Machine Learning · Computer Science 2022-09-30 Mohammad Rostami

We consider the computation of syzygies of multivariate polynomials in a finite-dimensional setting: for a $\mathbb{K}[X_1,\dots,X_r]$-module $\mathcal{M}$ of finite dimension $D$ as a $\mathbb{K}$-vector space, and given elements…

Symbolic Computation · Computer Science 2020-06-22 Vincent Neiger , Éric Schost

Solving systems of polynomial equations is a central problem in nonlinear and computational algebra. Since Buchberger's algorithm for computing Gr\"obner bases in the 60s, there has been a lot of progress in this domain. Moreover, these…

Symbolic Computation · Computer Science 2022-05-23 Matías R. Bender

In this article, we try to explain and unify standard divisibility tests found in various books. We then look at recurring decimals, and list a few of their properties. We show how to compute the number of digits in the recurring part of…

Number Theory · Mathematics 2011-08-01 Apoorva Khare

Despite the impressive advancements in modern machine learning, achieving robustness in Domain Generalization (DG) tasks remains a significant challenge. In DG, models are expected to perform well on samples from unseen test distributions…

Machine Learning · Computer Science 2025-07-08 Ron Tsibulsky , Daniel Nevo , Uri Shalit

Let $f_1,\ldots,f_m$ be elements in a quotient $R^n / N$ which has finite dimension as a $K$-vector space, where $R = K[X_1,\ldots,X_r]$ and $N$ is an $R$-submodule of $R^n$. We address the problem of computing a Gr\"obner basis of the…

Symbolic Computation · Computer Science 2020-06-05 Simone Naldi , Vincent Neiger

This is a system paper about a new GPLv2 open source C library GBLA implementing and improving the idea of Faug\`ere and Lachartre (GB reduction). We further exploit underlying structures in matrices generated during Gr\"obner basis…

Symbolic Computation · Computer Science 2016-02-22 Brice Boyer , Christian Eder , Jean-Charles Faugère , Sylvian Lachartre , Fayssal Martani

We present computational methods for constructing orthogonal/orthonormal polynomials over arbitrary polygonal domains in $\mathbb{R}^2$ using bivariate spline functions. Leveraging a mature MATLAB implementation which generates spline…

Numerical Analysis · Mathematics 2026-01-08 Ming-Jun Lai
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