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Related papers: Biorthogonal Extended Krylov Subspace Methods

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Reformulating computer vision problems over Riemannian manifolds has demonstrated superior performance in various computer vision applications. This is because visual data often forms a special structure lying on a lower dimensional space…

Computer Vision and Pattern Recognition · Computer Science 2015-09-21 Kun Zhao , Azadeh Alavi , Arnold Wiliem , Brian C. Lovell

We study the orthogonal projections of symplectic balls in $\mathbb{R}^{2n}$ on complex subspaces. In particular we show that these projections are themselves symplectic balls under a certain complexity assumption. Our main result is a…

Symplectic Geometry · Mathematics 2024-05-20 Nuno Costa Dias , Maurice A. de Gosson , Joao Nuno Prata

A class of (block) rational Krylov subspace based projection method for solving large-scale continuous-time algebraic Riccati equation (CARE) $0 = \mathcal{R}(X) := A^HX + XA + C^HC - XBB^HX$ with a large, sparse $A$ and $B$ and $C$ of full…

Numerical Analysis · Mathematics 2024-08-20 Christian Bertram , Heike Faßbender

We develop a rigorous theoretical framework for principal manifold estimation that recovers a latent low-dimensional manifold from a point cloud observed in a high-dimensional ambient space. Our framework accommodates manifolds with…

Statistics Theory · Mathematics 2026-04-07 Kun Meng , Christopher Perez

Space-time multivectors in Clifford algebra (space-time algebra) and their application to nonlinear electrodynamics are considered. Functional product and infinitesimal operators for translation and rotation groups are introduced, where…

High Energy Physics - Theory · Physics 2007-05-23 Alexander A. Chernitskii

In this paper we use some basic facts from the theory of (matrix) Lie groups and algebras to show that many of the classical matrix splittings used to construct stationary iterative methods and preconditioniers for Krylov subspace methods…

Numerical Analysis · Mathematics 2025-08-26 Michele Benzi , Milo Viviani

Krylov space methods provide an efficient framework for analyzing the dynamical aspects of quantum systems, with tridiagonal matrices playing a key role. Despite their importance, the behavior of such matrices from chaotic to integrable…

Quantum Physics · Physics 2025-02-13 Budhaditya Bhattacharjee , Pratik Nandy

In the framework of tensor spaces, we consider orthogonalization kernels to generate an orthogonal basis of a tensor subspace from a set of linearly independent tensors. In particular, we experimentally study the loss of orthogonality of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-17 Olivier Coulaud , Luc Giraud , Martina Iannacito

This paper presents a structure-preserving model reduction framework for linear systems, in which the $\mathcal{H}_2$ optimization is incorporated with the Petrov-Galerkin projection to preserve structural features of interest, including…

Optimization and Control · Mathematics 2023-02-20 Xiaodong Cheng

We construct rational elliptic surfaces of index two by explicitly constructing their associated Halphen pencils in the projective plane $\mathbb{P}^2$. For each of the types of singular fibers that occur we construct at least one example…

Algebraic Geometry · Mathematics 2020-08-20 Aline Zanardini

By recasting metrical geometry in a purely algebraic setting, both Euclidean and non-Euclidean geometries can be studied over a general field with an arbitrary quadratic form. Both an affine and a projective version of this new theory are…

Metric Geometry · Mathematics 2007-05-23 Norman J. Wildberger

We present a preconditioner based on spectral projection that is combined with a deflated Krylov subspace method for solving ill conditioned linear systems of equations. Our results show that the proposed algorithm requires many fewer…

Numerical Analysis · Mathematics 2016-09-23 Man-Chung Yeung , Craig C. Douglas , Long Lee

In this work, we propose a reduced basis method for efficient solution of parametric linear systems. The coefficient matrix is assumed to be a linear matrix-valued function that is symmetric and positive definite for admissible values of…

Numerical Analysis · Mathematics 2021-09-28 Antti Autio , Antti Hannukainen

Although equirectangular projection (ERP) is a convenient form to store omnidirectional images (also known as 360-degree images), it is neither equal-area nor conformal, thus not friendly to subsequent visual communication. In the context…

Image and Video Processing · Electrical Eng. & Systems 2021-12-28 Mu Li , Kede Ma , Jinxing Li , David Zhang

We analyze when an arbitrary matrix pencil is equivalent to a dissipative Hamiltonian pencil and show that this heavily restricts the spectral properties. In order to relax the spectral properties, we introduce matrix pencils with…

Numerical Analysis · Mathematics 2021-10-22 Christian Mehl , Volker Mehrmann , Michal Wojtylak

We present a primal-dual algorithmic framework to obtain approximate solutions to a prototypical constrained convex optimization problem, and rigorously characterize how common structural assumptions affect the numerical efficiency. Our…

Optimization and Control · Mathematics 2015-03-04 Quoc Tran-Dinh , Volkan Cevher

We provide algorithms to reconstruct rational ruled surfaces in three-dimensional projective space from the `apparent contour' of a single projection to the projective plane. We deal with the case of tangent developables and of general…

Symbolic Computation · Computer Science 2021-04-29 Matteo Gallet , Niels Lubbes , Josef Schicho , Jan Vršek

The 4-dimensional Sklyanin algebra is the homogeneous coordinate ring of a noncommutative analogue of projective 3-space. The degree-two component of the algebra contains a 2-dimensional subspace of central elements. The zero loci of those…

Quantum Algebra · Mathematics 2011-08-09 S. Paul Smith , M. Van den Bergh

In this paper, we consider optimization problems w.r.t. to pairs of orthogonal matrices $XY = I$. Problems of this form arise in several applications such as finding shape correspondence in computer graphics. We show that the space of such…

Optimization and Control · Mathematics 2016-09-15 Klaus Glashoff , Michael M. Bronstein

Krylov subspace methods, such as the Conjugate Gradient (CG) and BiCGSTAB methods, are widely used in scientific computing for solving linear systems. In this study, we propose a new framework for solving large Sylvester equations in a…

Numerical Analysis · Mathematics 2026-05-28 Yuki Satake , Takeshi Fukaya , Tomohiro Sogabe , Shao-Liang Zhang
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