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Jordan Normal Forms serve as excellent representatives of conjugacy classes of matrices over closed fields. Once we knows normal forms, we can compute functions of matrices, their main invariant, etc. The situation is much more complicated…

Number Theory · Mathematics 2021-07-07 Oleg Karpenkov

We study the smooth structure of convex functions by generalizing a powerful concept so-called self-concordance introduced by Nesterov and Nemirovskii in the early 1990s to a broader class of convex functions, which we call generalized…

Optimization and Control · Mathematics 2018-05-09 Tianxiao Sun , Quoc Tran-Dinh

We study the convergence of iterative linear solvers for discontinuous Galerkin discretizations of systems of hyperbolic conservation laws with polygonal mesh elements compared with that of traditional triangular elements. We solve the…

Numerical Analysis · Mathematics 2019-11-25 Will Pazner , Per-Olof Persson

The generalized Gearhart-Koshy acceleration is a recent exact affine search technique designed for the method of cyclic projections onto hyperplanes, i.e., the Kaczmarz method. However, its convergence properties, particularly the linear…

Numerical Analysis · Mathematics 2026-04-08 Yijie Wang , Yonghan Sun , Deren Han , Jiaxin Xie

Spectral averaging techniques for one-dimensional discrete Schroedinger operators are revisited and extended. In particular, simultaneous averaging over several parameters is discussed. Special focus is put on proving lower bounds on the…

Mathematical Physics · Physics 2016-10-28 Rafael del Rio , Carmen Martinez , Hermann Schulz-Baldes

In this paper, we present a unified analysis of the superconvergence property for a large class of mixed discontinuous Galerkin methods. This analysis applies to both the Poisson equation and linear elasticity problems with symmetric stress…

Numerical Analysis · Mathematics 2021-07-28 Limin Ma

The double-exponential Sinc-collocation method is known as a super-accurate method for solving initial value problems of ordinary differential equations, for which the error decreases almost exponentially as a function of the number of…

Numerical Analysis · Mathematics 2026-04-29 Yusaku Yamamoto , Ken'ichiro Tanaka

The Gromov-Wasserstein (GW) problem is an extension of the classical optimal transport problem to settings where the source and target distributions reside in incomparable spaces, and for which a cost function that attributes the price of…

Optimization and Control · Mathematics 2025-04-22 Hoang Anh Tran , Binh Tuan Nguyen , Yong Sheng Soh

This paper studies the polynomial optimization problem whose feasible set is a union of several basic closed semialgebraic sets. We propose a unified hierarchy of Moment-SOS relaxations to solve it globally. Under some assumptions, we prove…

Optimization and Control · Mathematics 2024-05-21 Jiawang Nie , Linghao Zhang

Incremental gradient and incremental proximal methods are a fundamental class of optimization algorithms used for solving finite sum problems, broadly studied in the literature. Yet, without strong convexity, their convergence guarantees…

Optimization and Control · Mathematics 2024-07-01 Xufeng Cai , Jelena Diakonikolas

In this work, the authors introduce a generalized weak Galerkin (gWG) finite element method for the time-dependent Oseen equation. The generalized weak Galerkin method is based on a new framework for approximating the gradient operator.…

Numerical Analysis · Mathematics 2022-09-14 Wenya Qi , Padmanabhan Seshaiyer , Junping Wang

The generalized Prony method introduced by Peter & Plonka (2013) is a reconstruction technique for a large variety of sparse signal models that can be represented as sparse expansions into eigenfunctions of a linear operator $A$. However,…

Numerical Analysis · Mathematics 2020-11-30 Kilian Stampfer , Gerlind Plonka

The extragradient (EG), introduced by G. M. Korpelevich in 1976, is a well-known method to approximate solutions of saddle-point problems and their extensions such as variational inequalities and monotone inclusions. Over the years,…

Optimization and Control · Mathematics 2023-03-31 Quoc Tran-Dinh

The relation between two Morse functions defined on a common domain can be studied in terms of their Jacobi set. The Jacobi set contains points in the domain where the gradients of the functions are aligned. Both the Jacobi set itself as…

Computational Geometry · Computer Science 2013-07-31 Harsh Bhatia , Bei Wang , Gregory Norgard , Valerio Pascucci , Peer-Timo Bremer

We develop an encompassing framework for matching, covariate balancing, and doubly-robust methods for causal inference from observational data called generalized optimal matching (GOM). The framework is given by generalizing a new…

Machine Learning · Statistics 2017-10-30 Nathan Kallus

The conjugate gradient (CG) method is an efficient iterative method for solving large-scale strongly convex quadratic programming (QP). In this paper we propose some generalized CG (GCG) methods for solving the $\ell_1$-regularized…

Optimization and Control · Mathematics 2016-02-15 Zhaosong Lu , Xiaojun Chen

The paper studies the convergence of some parallel multisplitting block iterative methods for the solution of linear systems arising in the numerical solution of Euler equations. Some sufficient conditions for convergence are proposed. As…

Numerical Analysis · Mathematics 2014-10-14 Cheng-yi Zhang , Shuanghua Luo , Zongben Xu

In this paper universality limits are studied in connection with measures which exhibit power-type singular behavior somewhere in their support. We extend the results of Lubinsky for Jacobi measures supported on $ [-1,1] $ to generalized…

Classical Analysis and ODEs · Mathematics 2016-05-16 Tivadar Danka

In this paper, we explain the convergence speed of different iteration schemes with the fluid diffusion view when solving a linear fixed point problem. This interpretation allows one to better understand why power iteration or Jacobi…

Numerical Analysis · Computer Science 2013-04-08 Dohy Hong

We deal with interval linear systems of equations. We present a new operator, which generalizes the interval Gauss-Seidel method. Also, based on the new operator and properties of the well-known methods, we propose a new algorithm, called…

Numerical Analysis · Mathematics 2019-05-27 Milan Hladík
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