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Matrix Factorization has emerged as a widely adopted framework for modeling data exhibiting low-rank structures. To address challenges in manifold learning, this paper presents a subspace-constrained quadratic matrix factorization model.…

Machine Learning · Computer Science 2024-11-08 Zheng Zhai , Xiaohui Li

This paper presents a canonical dual approach to the problem of minimizing the sum of a quadratic function and the ratio of nonconvex function and quadratic functions, which is a type of non-convex optimization problem subject to an…

Optimization and Control · Mathematics 2012-11-21 David Yang Gao , Ning Ruan

We prove that any function with real-valued coefficients, whose input is 4 binary variables and whose output is a real number, is perfectly equivalent to a quadratic function whose input is 5 binary variables and is minimized over the new…

Discrete Mathematics · Computer Science 2019-10-31 Nike Dattani , Hou Tin Chau

We use computational linear algebra and commutative algebra to study spaces of relations satisfied by quadrilinear operations. The relations are analogues of associativity in the sense that they are quadratic (every term involves two…

Rings and Algebras · Mathematics 2025-08-01 Murray R. Bremner , Juana Sánchez-Ortega

Solving dual quaternion equations is an important issue in many fields such as scientific computing and engineering applications. In this paper, we first introduce a new metric function for dual quaternion matrices. Then, we reformulate…

Optimization and Control · Mathematics 2024-11-11 Chen Ling , Chenjian Pan , Liqun Qi

Let $\mathfrak{R}$ and $\mathfrak{R}'$ be two associative rings (not necessarily with the identity elements). A bijective map $\varphi$ of $\mathfrak{R}$ onto $\mathfrak{R}'$ is called a \textit{$m$-multiplicative isomorphism} if {$\varphi…

Rings and Algebras · Mathematics 2022-06-01 Bruno L. M. Ferreira , Aisha Jabeen

We propose a functional view of matrix decomposition problems on graphs such as geometric matrix completion and graph regularized dimensionality reduction. Our unifying framework is based on the key idea that using a reduced basis to…

Machine Learning · Computer Science 2021-02-08 Abhishek Sharma , Maks Ovsjanikov

It turned out that the set of the fixed points is not necessarily the same as the set of the local minima of the energy functional. It depends on the diagonal elements of the connection matrix. The simple method which allows to cut off…

Disordered Systems and Neural Networks · Physics 2007-05-23 Leonid B. Litinskii

We consider the nonlinear integer programming problem of minimizing a quadratic function over the integer points in variable dimension satisfying a system of linear inequalities. We show that when the Graver basis of the matrix defining the…

Optimization and Control · Mathematics 2014-05-08 Jon Lee , Shmuel Onn , Lyubov Romanchuk , Robert Weismantel

Recently there has been several works estimating the number of $n\times n$ matrices with elements from some finite sets $\mathcal X$ of arithmetic interest and of a given determinant. Typically such results are compared with the trivial…

Number Theory · Mathematics 2024-08-09 Ilya D. Shkredov , Igor E. Shparlinski

Mixed-integer quadratic programming is the problem of optimizing a quadratic function over points in a polyhedral set where some of the components are restricted to be integral. In this paper, we prove that the decision version of…

Discrete Mathematics · Computer Science 2014-07-21 Alberto Del Pia , Santanu S. Dey , Marco Molinaro

Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image…

Optimization and Control · Mathematics 2012-08-13 Nicolas Gillis , François Glineur

In this paper, we demonstrate that several classes of functions, specifically n-multiplicative isomorphisms, derivations, elementary maps, and Jordan elementary maps on a class of algebras that includes Jordan algebras with idempotents,…

Rings and Algebras · Mathematics 2025-03-31 Daniel Eiti Nishida Kawai , Henrique Guzzo , Bruno Leonardo Macedo Ferreira

An $n$-ary associative function is called reducible if it can be written as a composition of a binary associative function. We summarize known results when the function is defined on a chain and is nondecreasing. Our main result shows that…

Rings and Algebras · Mathematics 2018-09-05 Gergely Kiss , Gábor Somlai

Completing a data matrix X has become an ubiquitous problem in modern data science, with applications in recommender systems, computer vision, and networks inference, to name a few. One typical assumption is that X is low-rank. A more…

Machine Learning · Computer Science 2018-08-03 Daniel L. Pimentel-Alarcón

The neutrino mixing matrix is expanded in powers of a small parameter $\lambda$ in tri-bimaximal mixing pattern. We also present some applications of this parametrization, such as to the expression of the Jarlskog parameter $J$. Comparing…

High Energy Physics - Phenomenology · Physics 2014-11-18 Nan Li , Bo-Qiang Ma

The connected sum of two flat virtual knots depends on the choice of diagrams and basepoints. We show that any minimal crossing diagram of a composite flat virtual knot is a connected sum diagram. We also show the crossing number of flat…

Geometric Topology · Mathematics 2024-07-26 Jie Chen

The multiplicative and additive compounds of a matrix play an important role in several fields of mathematics including geometry, multi-linear algebra, combinatorics, and the analysis of nonlinear time-varying dynamical systems. There is a…

Optimization and Control · Mathematics 2022-04-05 Eyal Bar-Shalom , Omri Dalin , Michael Margaliot

The quadratic minimum spanning tree problem and its variations such as the quadratic bottleneck spanning tree problem, the minimum spanning tree problem with conflict pair constraints, and the bottleneck spanning tree problem with conflict…

Data Structures and Algorithms · Computer Science 2016-03-16 Ante Ćustić , Ruonan Zhang , Abraham P. Punnen

Alternating minimization represents a widely applicable and empirically successful approach for finding low-rank matrices that best fit the given data. For example, for the problem of low-rank matrix completion, this method is believed to…

Machine Learning · Statistics 2012-12-04 Prateek Jain , Praneeth Netrapalli , Sujay Sanghavi