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Multi-label learning is usually used to mine the correlation between features and labels, and feature selection can retain as much information as possible through a small number of features. $\ell_{2,1}$ regularization method can get sparse…

Machine Learning · Statistics 2023-03-31 Haibao Li , Hongzhi Zhai

Valiant introduced some 25 years ago an algebraic model of computation along with the complexity classes VP and VNP, which can be viewed as analogues of the classical classes P and NP. They are defined using non-uniform sequences of…

Discrete Mathematics · Computer Science 2007-06-13 Laurent Lyaudet , Pascal Koiran , Uffe Flarup

We present a general framework for constructing polynomial integrable systems on linearizations of Poisson varieties that admit log-canonical systems. Our construction is in particular applicable to Poisson varieties with compatible cluster…

Symplectic Geometry · Mathematics 2026-03-30 Yanpeng Li , Yu Li , Jiang-Hua Lu

In Ehrhart theory, the well-known sign pattern problem asks: given a positive integer $d\geq 3$ and integers $1 \leq i_1 < \cdots < i_k \leq d-2$, does there exist a $d$-dimensional integral polytope $\mathcal{P}$ such that in its Ehrhart…

Combinatorics · Mathematics 2026-05-26 Feihu Liu , Sihao Tao , Guoce Xin

It is well-known that the convex and concave envelope of a multilinear polynomial over a box are polyhedral functions. Exponential-sized extended and projected formulations for these envelopes are also known. We consider the convexification…

Optimization and Control · Mathematics 2021-06-14 Yibo Xu , Warren Adams , Akshay Gupte

In this paper, we consider the exact/approximate general joint block diagonalization (GJBD) problem of a matrix set $\{A_i\}_{i=0}^p$ ($p\ge 1$), where a nonsingular matrix $W$ (often referred to as diagonalizer) needs to be found such that…

Numerical Analysis · Mathematics 2017-04-20 Yunfeng Cai , Guanghui Cheng , Decai Shi

Let $R$ be a commutative unital ring. A well-known factorization problem is whether any matrix in $\mathrm{SL}_n(R)$ is a product of elementary matrices with entries in $R$. To solve the problem, we use two approaches based on the notion of…

Commutative Algebra · Mathematics 2019-02-12 Evgueni Doubtsov , Frank Kutzschebauch

Let $\mathrm{R}$ be a real closed field and $\mathrm{D} \subset \mathrm{R}$ an ordered domain. We consider the algorithmic problem of computing the generalized Euler-Poincar\'e characteristic of real algebraic as well as semi-algebraic…

Algebraic Geometry · Mathematics 2017-07-13 Saugata Basu , Cordian Riener

In this paper, we investigate a class of nonlinear eigenvalue problems resulting from quantum physics. We first prove that the eigenfunction cannot be a polynomial on any open set, which may be reviewed as a refinement of the classic unique…

Numerical Analysis · Mathematics 2019-07-11 Bin Yang , Aihui Zhou

Renormalized homotopy continuation on toric varieties is introduced as a tool for solving sparse systems of polynomial equations, or sparse systems of exponential sums. The cost of continuation depends on a renormalized condition length,…

Numerical Analysis · Mathematics 2025-06-23 Gregorio Malajovich

In this paper we consider generalized eigenvalue problems for a family of operators with a polynomial dependence on a complex parameter. This problem is equivalent to a genuine non self-adjoint operator. We discuss here existence of non…

Mathematical Physics · Physics 2007-05-23 Didier Robert

Differential systems with a Fuchsian linear part are studied in regions including all the singularities in the complex plane of these equations. Such systems are not necessarily analytically equivalent to their linear part (they are not…

Classical Analysis and ODEs · Mathematics 2008-08-27 Rodica D. Costin

We discuss computing with hierarchies of families of (potentially weighted) semiclassical Jacobi polynomials which arise in the construction of multivariate orthogonal polynomials. In particular, we outline how to build connection and…

Numerical Analysis · Mathematics 2024-07-11 Ioannis P. A. Papadopoulos , Timon S. Gutleb , Richard M. Slevinsky , Sheehan Olver

We generalize several important results from the perturbation theory of linear operators to the setting of semisimple orthogonal symmetric Lie algebras. These Lie algebras provide a unifying framework for various notions of matrix…

Representation Theory · Mathematics 2023-07-04 Emanuel Malvetti , Gunther Dirr , Frederik vom Ende , Thomas Schulte-Herbrüggen

Using the braided version of Lawvere's algebraic theories and Mac Lane's PROPs, we introduce polynomial identities for arbitrary algebraic structures in a braided monoidal category C as well as their codimensions in the case when C is…

Rings and Algebras · Mathematics 2024-12-13 A. S. Gordienko

This paper provides the spectral decomposition of $(\star,\epsilon)$-palindromic quadratic matrix polynomial $P(\lambda)$ by a standard pair and a parameter matrix. When $J$ is assumed to be a block diagonal matrix, the parameter matrix…

Numerical Analysis · Mathematics 2026-05-08 Kang Zhao , Xin Wang , Xiaoxiao Ma

Parametric linear systems are linear systems of equations in which some symbolic parameters, that is, symbols that are not considered to be candidates for elimination or solution in the course of analyzing the problem, appear in the…

Rings and Algebras · Mathematics 2025-09-01 Robert M. Corless , Mark Giesbrecht , Leili Rafiee Sevyeri , B. David Saunders

We present a method to linearize, without approximation, a specific class of eigenvalue problems with eigenvector nonlinearities (NEPv), where the nonlinearities are expressed by scalar functions that are defined by a quotient of linear…

Numerical Analysis · Mathematics 2021-05-24 Rob Claes , Elias Jarlebring , Karl Meerbergen , Parikshit Upadhyaya

In continuation to our recent work on noncommutative polynomial factorization, we consider the factorization problem for matrices of polynomials and show the following results. (1) Given as input a full rank $d\times d$ matrix $M$ whose…

Computational Complexity · Computer Science 2022-04-01 V. Arvind , Pushkar S. Joglekar

Spectral methods are popular in detecting global structures in the given data that can be represented as a matrix. However when the data matrix is sparse or noisy, classic spectral methods usually fail to work, due to localization of…

Machine Learning · Statistics 2016-09-12 Pan Zhang
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