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Submodular functions describe a variety of discrete problems in machine learning, signal processing, and computer vision. However, minimizing submodular functions poses a number of algorithmic challenges. Recent work introduced an…

Optimization and Control · Mathematics 2014-11-06 Robert Nishihara , Stefanie Jegelka , Michael I. Jordan

We describe and implement an algorithm to find all post-critically finite (PCF) cubic polynomials defined over $\mathbb{Q}$, up to conjugacy over $\text{PGL}_2(\bar{\mathbb{Q}})$. We describe normal forms that classify equivalence classes…

Number Theory · Mathematics 2020-06-18 Jacqueline Anderson , Michelle Manes , Bella Tobin

One of the few available complete methods for checking the satisfiability of sets of polynomial constraints over the reals is the cylindrical algebraic covering (CAlC) method. In this paper, we propose an extension for this method to…

Symbolic Computation · Computer Science 2023-06-30 Philipp Bär , Jasper Nalbach , Erika Ábrahám , Christopher W. Brown

We prove a lower bound on the canonical height associated to polynomials over number fields evaluated at points with infinite forward orbit. The lower bound depends only on the degree of the polynomial, the degree of the number field, and…

Number Theory · Mathematics 2017-09-27 Nicole Looper

We study a generalized nonconvex Burer-Monteiro formulation for low-rank minimization problems. We use recent results on non-Euclidean first order methods to provide efficient and scalable algorithms. Our approach uses geometries induced by…

Optimization and Control · Mathematics 2021-02-18 Radu-Alexandru Dragomir , Alexandre d'Aspremont , Jérôme Bolte

Quadratic interpolation models and simplex derivatives are fundamental tools in numerical optimization, particularly in derivative-free optimization. When constructed in suitably chosen affine subspaces, these tools have been shown to be…

Optimization and Control · Mathematics 2026-02-12 Yiwen Chen

Recent works have shown that quantum computers can polynomially speed up certain SAT-solving algorithms even when the number of available qubits is significantly smaller than the number of variables. Here we generalise this approach. We…

Quantum Physics · Physics 2020-02-19 Yimin Ge , Vedran Dunjko

Matrix factorization methods are important tools in data mining and analysis. They can be used for many tasks, ranging from dimensionality reduction to visualization. In this paper we concentrate on the use of matrix factorizations for…

Machine Learning · Computer Science 2017-07-28 Sanjar Karaev , Pauli Miettinen

The method of subquotients is developed and used to determine all finite dimensional rank 2 Nichols algebras of diagonal type over an arbitrary field of characteristic zero. Key Words: Hopf algebra, Nichols algebra

Quantum Algebra · Mathematics 2016-09-07 I. Heckenberger

In this paper we prove some results on the possible multiplicative orders of $\alpha + \alpha^{-1}$ when $\alpha$ is a non-zero element of a finite field of characteristic 2. The results of the paper rely on a previous investigation on the…

Number Theory · Mathematics 2021-08-11 Simone Ugolini

Cylindrical Algebraic Decomposition (CAD) algorithms typically produce a decomposition adapted to a finite family of semi-algebraic sets $\mathcal{F}$ (i.e. every member of $\mathcal{F}$ is a union of cells). Different algorithms may…

Symbolic Computation · Computer Science 2026-05-07 Lucas Michel

We construct a convergent family of outer approximations for the problem of optimizing polynomial functions over convex bodies subject to polynomial constraints. This is achieved by generalizing the polarization hierarchy, which has…

Optimization and Control · Mathematics 2024-06-17 Martin Plávala , Laurens T. Ligthart , David Gross

We investigate the geometric properties of hyperbolic affine flat, affine minimal surfaces in the equiaffine space $\mathbb{A}^3$. We use Cartan's method of moving frames to compute a complete set of local invariants for such surfaces.…

Differential Geometry · Mathematics 2013-08-02 Jeanne N. Clelland , Jonah M. Miller

We continue our study of minimal affinizations for algebras of type D, E.

High Energy Physics - Theory · Physics 2009-10-28 V. Chari , A. N. Pressley

The purpose of this paper is to study some new concrete approximation processes for continuous vector-valued mappings defined on the infinite dimensional cube or on a subset of a real Hilbert space. In both cases these operators are…

Functional Analysis · Mathematics 2010-05-27 Lorenzo D'Ambrosio

Extending the wavenumber-explicit analysis of [Chen & Qiu, J. Comput. Appl. Math. 309 (2017)], we analyze the $L^2$-convergence of a least squares method for the Helmholtz equation with wavenumber $k$. For domains with an analytic boundary,…

Numerical Analysis · Mathematics 2024-07-25 Maximilian Bernkopf , Jens Markus Melenk

Minimal Q-graded subalgebras of semisimple Lie algebras are introduced, and it is proved that their derived algebras are abelian. Almost inner derivations of minimal Q-graded subalgebras are investigated, they are all inner derivations.…

Representation Theory · Mathematics 2025-12-17 Yaxin Shen , Xiandong Wang

This paper presents an algorithmic framework for the minimization of strictly convex quadratic functions. The framework is flexible and generic. At every iteration the search direction is a linear combination of the negative gradient, as…

Optimization and Control · Mathematics 2025-05-08 Liam MacDonald , Rua Murray , Rachael Tappenden

This paper deals with some nonlinear problems which exponential and biexponential decays are involved in. A proof of the quasiconvexity of the error function in some of these problems of optimization is presented. This proof is restricted…

A theorem is proved concerning approximation of analytic functions by multivariate polynomials in the $s$-dimensional hypercube. The geometric convergence rate is determined not by the usual notion of degree of a multivariate polynomial,…

Numerical Analysis · Mathematics 2016-08-09 Lloyd N. Trefethen