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A pseudo-Boolean function is a real-valued function $f(x)=f(x_1,x_2,\ldots,x_n)$ of $n$ binary variables; that is, a mapping from $\{0,1\}^n$ to $\mathbb{R}$. For a pseudo-Boolean function $f(x)$ on $\{0,1\}^n$, we say that $g(x,y)$ is a…

Optimization and Control · Mathematics 2014-04-29 Martin Anthony , Endre Boros , Yves Crama , Aritanan Gruber

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a…

Probability · Mathematics 2013-04-03 Gilles Pagès

Algorithms and hardware for solving quadratic unconstrained binary optimization (QUBO) problems have made significant recent progress. This advancement has focused attention on formulating combinatorial optimization problems as quadratic…

Machine Learning · Computer Science 2025-08-26 Yuta Shikuri

We consider the problem of optimizing a multivariate quadratic function where each decision variable is constrained to be a complex $m$'th root of unity. Such problems have applications in signal processing, MIMO detection, and the…

Optimization and Control · Mathematics 2025-08-05 Ahmad Al-Sulami , Hamza Fawzi , Shengding Sun

This paper presents a quadratic formula-based nonlinear representation for a given single-variable function f(x), $-1 \leq x \leq 1$. First, we construct the explicit polynomial coefficient functions a(x), b(x), and c(x) using a…

Numerical Analysis · Mathematics 2025-12-09 Ziqin He , Can Chen , Min Hyung Cho , Jingfang Huang , Yichao Wu

Quadratization is a transform of a system of ODEs with polynomial right-hand side into a system of ODEs with at most quadratic right-hand side via the introduction of new variables. It has been recently used as a pre-processing step for new…

Dynamical Systems · Mathematics 2020-11-10 Foyez Alauddin

Quadratic Unconstrained Binary Optimization models are useful for solving a diverse range of optimization problems. Constraints can be added by incorporating quadratic penalty terms into the objective, often with the introduction of slack…

Optimization and Control · Mathematics 2021-05-18 Amit Verma , Mark Lewis

We consider a generalization of polynomial programs: algebraic programs, which are optimization or feasibility problems with algebraic objectives or constraints. Algebraic functions are defined as zeros of multivariate polynomials. They are…

Optimization and Control · Mathematics 2025-02-13 Muhammad Maaz , Adam W. Strzeboński

We extend to several variables an earlier result of ours, according to which an entire function of one variable of sufficiently small exponential type, having all derivatives of even order taking integer values at two points, is a…

Complex Variables · Mathematics 2021-12-07 Michel Waldschmidt

The main outcomes of the paper are divided into two parts. First, we present a new dual for quadratic programs, in which, the dual variables are affine functions, and we prove strong duality. Since the new dual is intractable, we consider a…

Optimization and Control · Mathematics 2019-01-31 Moslem Zamani

Binary quadratic programming problems have attracted much attention in the last few decades due to their potential applications. This type of problems are NP-hard in general, and still considered a challenge in the design of efficient…

Data Structures and Algorithms · Computer Science 2014-11-20 Khaled Elbassioni , Trung Thanh Nguyen

Here we show how universal quantum computers based on the quantum circuit model can handle mathematical analysis calculations for functions with continuous domains, without any digitalization, and with remarkably few qubits. The basic…

Quantum Physics · Physics 2022-10-10 Pablo Bermejo , Roman Orus

Quadratic Unconstrained Binary Optimization (QUBO) is recognized as a unifying framework for modeling a wide range of problems. Problems can be solved with commercial solvers customized for solving QUBO and since QUBO have degree two, it is…

Optimization and Control · Mathematics 2021-07-27 Amit Verma , Mark Lewis , Gary Kochenberger

A sampling-based optimization method for quadratic functions is proposed. Our method approximately solves the following $n$-dimensional quadratic minimization problem in constant time, which is independent of $n$: $z^*=\min_{\mathbf{v} \in…

Machine Learning · Computer Science 2016-09-02 Kohei Hayashi , Yuichi Yoshida

For bivariate polynomials of degree $n\le 5$ we give fast numerical constructions of determinantal representations with $n\times n$ matrices. Unlike some other available constructions, our approach returns matrices of the smallest possible…

Numerical Analysis · Mathematics 2023-09-18 Anita Buckley , Bor Plestenjak

Quadratization of polynomial and nonpolynomial systems of ordinary differential equations is advantageous in a variety of disciplines, such as systems theory, fluid mechanics, chemical reaction modeling and mathematical analysis. A…

Symbolic Computation · Computer Science 2023-12-07 Andrey Bychkov , Opal Issan , Gleb Pogudin , Boris Kramer

The problem of minimization of a quadratic functional depending on great number of binary variables is examined. 3 variants of minimization procedure are studied with the aid of computer simulation for spin-glass matrices. It is shown that…

Disordered Systems and Neural Networks · Physics 2009-07-16 Leonid B. Litinskii

An integral quadratic form is called strictly $n$-regular if it primitively represents all quadratic forms in $n$ variables that are primitively represented by its genus. For any $n \geq 2$, it will be shown that there are only finitely…

Number Theory · Mathematics 2017-06-14 Wai Kiu Chan , Alicia Marino

Quadratization problem is, given a system of ODEs with polynomial right-hand side, transform the system to a system with quadratic right-hand side by introducing new variables. Such transformations have been used, for example, as a…

Symbolic Computation · Computer Science 2021-05-14 Andrey Bychkov , Gleb Pogudin

Submodular function minimization is a key problem in a wide variety of applications in machine learning, economics, game theory, computer vision, and many others. The general solver has a complexity of $O(n^3 \log^2 n . E +n^4 {\log}^{O(1)}…

Data Structures and Algorithms · Computer Science 2017-01-25 Srikumar Ramalingam , Chris Russell , Lubor Ladicky , Philip H. S. Torr
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