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This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the…

Numerical Analysis · Mathematics 2013-10-22 Kenneth Lange , Hua Zhou

Weighted projective spaces are natural generalizations of projective spaces with a rich structure. Projective Reed-Muller codes are error-correcting codes that played an important role in reliably transmitting information on digital…

Information Theory · Computer Science 2023-11-07 Yağmur Çakıroğlu , Mesut Şahin

Given a graph $G$, the $G$-parking function ideal $M_G$ is an artinian monomial ideal in the polynomial ring $S$ with the property that a linear basis for $S/M_G$ is provided by the set of $G$-parking functions. It follows that the…

Combinatorics · Mathematics 2018-06-18 Anton Dochtermann

We generalise Gabidulin codes to the case of infinite fields, eventually with characteristic zero. For this purpose, we consider an abstract field extension and any automorphism in the Galois group. We derive some conditions on the…

Information Theory · Computer Science 2017-03-28 Daniel Augot , Pierre Loidreau , Gwezheneg Robert

For any finite field ${\mathbb F}_q$ with $q$ elements, we study the set ${\mathcal F}_{(q,m)}$ of functions from ${\mathbb F}_q^m$ into ${\mathbb F}^q$. We introduce a transformation that allows us to determine a linear system of $q^{m+1}$…

Information Theory · Computer Science 2015-12-16 Miriam Abdon , Robert Rolland

We give a complete conjectural formula for the number $e_r(d,m)$ of maximum possible ${\mathbb{F}}q$-rational points on a projective algebraic variety defined by $r$ linearly independent homogeneous polynomial equations of degree $d$ in…

Algebraic Geometry · Mathematics 2022-03-23 Peter Beelen , Mrinmoy Datta , Sudhir R. Ghorpade

We develop and analyze the Generalized Multiplicative Gradient (GMG) method for solving a class of convex optimization problems over symmetric cones, where the objective function does not have Lipschitz gradient over the feasible region.…

Optimization and Control · Mathematics 2026-03-06 Renbo Zhao

Heged\H{u}s's lemma is the following combinatorial statement regarding polynomials over finite fields. Over a field $\mathbb{F}$ of characteristic $p > 0$ and for $q$ a power of $p$, the lemma says that any multilinear polynomial $P\in…

Computational Complexity · Computer Science 2023-06-22 Srikanth Srinivasan

The classical Remez inequality bounds the maximum of the absolute value of a polynomial $P(x)$ of degree $d$ on $[-1,1]$ through the maximum of its absolute value on any subset $Z$ of positive measure in $[-1,1]$. It was shown in…

Complex Variables · Mathematics 2011-02-15 Yosef Yomdin

This paper considers the minimization of a general objective function $f(X)$ over the set of rectangular $n\times m$ matrices that have rank at most $r$. To reduce the computational burden, we factorize the variable $X$ into a product of…

Information Theory · Computer Science 2018-07-04 Zhihui Zhu , Qiuwei Li , Gongguo Tang , Michael B. Wakin

Higher-order Fourier analysis, developed over prime fields, has been recently used in different areas of computer science, including list decoding, algorithmic decomposition and testing. We extend the tools of higher-order Fourier analysis…

Data Structures and Algorithms · Computer Science 2015-05-05 Arnab Bhattacharyya , Abhishek Bhowmick

We study properties of rank metric and codes in rank metric over finite fields. We show that in rank metric perfect codes do not exist. We derive an existence bound that is the equivalent of the Gilbert--Varshamov bound in Hamming metric.…

Discrete Mathematics · Computer Science 2007-07-13 P. Loidreau

The gradient discretisation method (GDM) is a generic framework designed recently, as a discretise in spatial space, to partial differential equations. This paper aims to use the GDM to establish a first general error estimate for numerical…

Numerical Analysis · Mathematics 2020-09-22 Yahya Alnashri

We consider the dynamics of gradient descent (GD) in overparameterized single hidden layer neural networks with a squared loss function. Recently, it has been shown that, under some conditions, the parameter values obtained using GD achieve…

Machine Learning · Computer Science 2021-05-17 Siddhartha Satpathi , R Srikant

A generalized conditional gradient method for minimizing the sum of two convex functions, one of them differentiable, is presented. This iterative method relies on two main ingredients: First, the minimization of a partially linearized…

Optimization and Control · Mathematics 2021-10-01 Karl Kunisch , Daniel Walter

In this paper, a distance between the Gaussian Mixture Models(GMMs) is obtained based on an embedding of the K-component Gaussian Mixture Model into the manifold of the symmetric positive definite matrices. Proof of embedding of K-component…

Differential Geometry · Mathematics 2025-01-14 Amit Vishwakarma , KS Subrahamanian Moosath

Composite function minimization captures a wide spectrum of applications in both computer vision and machine learning. It includes bound constrained optimization, $\ell_1$ norm regularized optimization, and $\ell_0$ norm regularized…

Numerical Analysis · Computer Science 2018-06-11 Ganzhao Yuan , Wei-Shi Zheng , Li Shen , Bernard Ghanem

Let $I$ be a homogeneous ideal in the polynomial ring $R = k[z_1, \cdots, z_n]$ , where $k$ is an algebraically closed field of characteristic zero. Macaulay's Theorem provides constraints on the Hilbert function of $I$ or $R/I$ from one…

Complex Variables · Mathematics 2025-12-29 Yun Gao

Based on Colombeau's theory of algebras of generalized functions we introduce the concepts of generalized functions taking values in differentiable manifolds as well as of generalized vector bundle homomorphisms. We study their basic…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger

We propose a unified theory of generalized weights for linear codes endowed with an arbitrary distance. Instead of relying on supports or anticodes, the weights of a code are defined via the intersections of the code with a chosen family of…

Information Theory · Computer Science 2025-12-22 Andrea Di Giusto , Elisa Gorla , Alberto Ravagnani