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For each square matrix polynomial $P(\lambda)$ of odd degree, a block-symmetric block-tridiagonal pencil $\mathcal{T}_{P}(\lambda)$ was introduced by Antoniou and Vologiannidis in 2004, and a variation $\mathcal{R}_P(\lambda)$ was…

Numerical Analysis · Mathematics 2017-06-14 M. I. Bueno , F. M. Dopico , S. Furtado , L. Medina

This paper adapts the recently developed rigorous application of the supersymmetric transfer matrix approach for the 1d band matrices to the case of the orthogonal symmetry. We consider $N\times N$ block band matrices consisting of $W\times…

Mathematical Physics · Physics 2020-11-30 Tatyana Shcherbina

In this paper, we explore optimal disturbances of blockings in the equivalent barotropic atmosphere using the conditional nonlinear optimal perturbation (CNOP) approach. Considering the initial blocking amplitude, the optimal disturbance…

Atmospheric and Oceanic Physics · Physics 2023-10-17 Bin Shi , Dehai Luo , Wenqi Zhang

This paper investigates the \emph{Wiring Diagram Problem} (WDP), a three-dimensional layout design problem arising in industrial applications such as cable harness design and pipeline routing in constrained environments. In these settings,…

Optimization and Control · Mathematics 2026-03-10 Víctor Blanco , Gabriel González , Justo Puerto

We call a matrix completely mixable if the entries in its columns can be permuted so that all row sums are equal. If it is not completely mixable, we want to determine the smallest maximal and largest minimal row sum attainable. These…

Optimization and Control · Mathematics 2015-01-06 Utz-Uwe Haus

We revisit the operator mixing in massless QCD-like theories. In particular, we address the problem of determining under which conditions a renormalization scheme exists where the renormalized mixing matrix in the coordinate representation,…

High Energy Physics - Theory · Physics 2021-08-27 Marco Bochicchio

We provide a solution to the problem of simultaneous $diagonalization$ $via$ $congruence$ of a given set of $m$ complex symmetric $n\times n$ matrices $\{A_{1},\ldots,A_{m}\}$, by showing that it can be reduced to a possibly…

Optimization and Control · Mathematics 2021-02-10 Miguel D. Bustamante , Pauline Mellon , M. Victoria Velasco

The assumption of independent subvectors arises in many aspects of multivariate analysis. In most real-world applications, however, we lack prior knowledge about the number of subvectors and the specific variables within each subvector.…

Methodology · Statistics 2024-01-23 Jan O. Bauer

Polynomial minimal bases of rational vector subspaces are a classical concept that plays an important role in control theory, linear systems theory, and coding theory. It is a common practice to arrange the vectors of any minimal basis as…

Numerical Analysis · Mathematics 2016-12-13 Paul Van Dooren , Froilán M. Dopico

In this paper, we revisit the solving bias when evaluating models on current Math Word Problem (MWP) benchmarks. However, current solvers exist solving bias which consists of data bias and learning bias due to biased dataset and improper…

Artificial Intelligence · Computer Science 2022-10-10 Zhicheng Yang , Jinghui Qin , Jiaqi Chen , Xiaodan Liang

The present paper studies a kind of robust optimization problems with constraint. The problem is formulated through Backward Stochastic Differential Equations (BSDEs) with quadratic generators. A necessary condition is established for the…

Optimization and Control · Mathematics 2024-02-14 Peng Luo , Alexander Schied , Xiaole Xue

Model predictive control problems for constrained hybrid systems are usually cast as mixed-integer optimization problems (MIP). However, commercial MIP solvers are designed to run on desktop computing platforms and are not suited for…

Optimization and Control · Mathematics 2020-02-05 Damian Frick , Angelos Georghiou , Juan L. Jerez , Alexander Domahidi , Manfred Morari

The research on spectral inequalities for discrete Schrodinger Operators has proved fruitful in the last decade. Indeed, several authors analysed the operator's canonical relation to a tridiagonal Jacobi matrix operator. In this paper, we…

Functional Analysis · Mathematics 2013-12-09 Arman Sahovic

Many practical problems involve the recovery of a binary matrix from partial information, which makes the binary matrix completion (BMC) technique received increasing attention in machine learning. In particular, we consider a special case…

Machine Learning · Computer Science 2019-04-09 Chunsheng Liu

Irregular conformal block is an important tool to study a new type of conformal theories, which can be constructed as the colliding limit of the regular conformal block. The irregular conformal block is realized as the $\beta$-deformed…

High Energy Physics - Theory · Physics 2015-06-18 Sang-Kwan Choi , Chaiho Rim

Metric Differential Privacy (mDP) extends the concept of Differential Privacy (DP) to serve as a new paradigm of data perturbation. It is designed to protect secret data represented in general metric space, such as text data encoded as word…

Artificial Intelligence · Computer Science 2024-05-10 Chenxi Qiu

The balanced incomplete block design (BIBD) problem is a difficult combinatorial problem with a large number of symmetries, which add complexity to its resolution. In this paper, we propose a dual (integer) problem representation that…

Neural and Evolutionary Computing · Computer Science 2024-11-05 David Rodríguez Rueda , Carlos Cotta , Antonio J. Fernández-Leiva

In this paper we study higher-order difference equations which can be written as follows: $$ \mathbf{J} (y_0,y_1,...)^T = \lambda^N (y_0,y_1,...)^T, $$ where $\mathbf{J}$ is a $(2N+1)$-diagonal bounded banded matrix…

Classical Analysis and ODEs · Mathematics 2026-04-17 Sergey M. Zagorodnyuk

A family of symmetric matrices $A_1,\ldots, A_d$ is SDC (simultaneous diagonalization by congruence, also called non-orthogonal joint diagonalization) if there is an invertible matrix $X$ such that every $X^T A_k X$ is diagonal. In this…

Numerical Analysis · Mathematics 2025-04-30 Haoze He , Daniel Kressner

We consider the problem of precision matrix estimation where, due to extraneous confounding of the underlying precision matrix, the data are independent but not identically distributed. While such confounding occurs in many scientific…

Machine Learning · Statistics 2019-07-01 Sinong Geng , Mladen Kolar , Oluwasanmi Koyejo
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