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We analyze a modified version of Nesterov accelerated gradient algorithm, which applies to affine fixed point problems with non self-adjoint matrices, such as the ones appearing in the theory of Markov decision processes with discounted or…

Optimization and Control · Mathematics 2021-07-05 Marianne Akian , Stéphane Gaubert , Zheng Qu , Omar Saadi

We propose a framework to use Nesterov's accelerated method for constrained convex optimization problems. Our approach consists of first reformulating the original problem as an unconstrained optimization problem using a continuously…

Optimization and Control · Mathematics 2021-03-12 Priyank Srivastava , Jorge Cortes

This paper investigates the existence of positive solutions for regular discrete second-order single-variable boundary value problems with mixed boundary conditions, including a nonhomogeneous Dirichlet boundary condition, of the form:…

Classical Analysis and ODEs · Mathematics 2025-06-23 Shalmali Bandyopadhyay , Kyle Byassee , Curt Lynch

We propose a variant of the classical conditional gradient method for sparse inverse problems with differentiable measurement models. Such models arise in many practical problems including superresolution, time-series modeling, and matrix…

Optimization and Control · Mathematics 2015-07-07 Nicholas Boyd , Geoffrey Schiebinger , Benjamin Recht

A new formulation of boundary value problems in gradient elasticity is presented in this work. The main outcome is the construction of partial differential systems of second order, which are typically equivalent with the well known fourth…

Analysis of PDEs · Mathematics 2019-09-25 Antonios Charalambopoulos , Evanthia Douka , Stelios Mavratzas

We consider the linear least squares problem with linear equality constraints (LSE problem) formulated as $\min_{x\in\mathbb{R}^{n}}\|Ax-b\|_2 \ \mathrm{s.t.} \ Cx = d$. Although there are some classical methods available to solve this…

Numerical Analysis · Mathematics 2025-01-06 Haibo Li

Despite their frequent slow convergence, proximal gradient schemes are widely used in large-scale optimization tasks due to their tremendous stability, scalability, and ease of computation. In this paper, we develop and investigate a…

Computation · Statistics 2025-08-19 Nicholas C. Henderson , Ravi Varadhan

Krylov subspace methods are widely known as efficient algebraic methods for solving large scale linear systems. However, on massively parallel hardware the performance of these methods is typically limited by communication latency rather…

Numerical Analysis · Computer Science 2018-08-22 Siegfried Cools

This paper proposes a collocation boundary element method based on the Burton--Miller method for solving transmission problems, which is rapidly convergent within the Krylov subspace solver framework. Our study enhances Burton--Miller-type…

Numerical Analysis · Mathematics 2025-01-17 Yasuhiro Matsumoto , Akihiro Yoshiki , Hiroshi Isakari

Iterative solvers for large-scale linear systems such as Krylov subspace methods can diverge when the linear system is ill-conditioned, thus significantly reducing the applicability of these iterative methods in practice for…

Numerical Analysis · Mathematics 2025-07-24 Vasileios Kalantzis , Mark S. Squillante , Chai Wah Wu

We propose an unconstrained optimization method based on the well-known primal-dual hybrid gradient (PDHG) algorithm. We first formulate the optimality condition of the unconstrained optimization problem as a saddle point problem. We then…

Optimization and Control · Mathematics 2024-08-29 X. Zuo , S. Osher , W. Li

A delay Lyapunov matrix corresponding to an exponentially stable system of linear time-invariant delay differential equations can be characterized as the solution of a boundary value problem involving a matrix valued delay differential…

Numerical Analysis · Mathematics 2018-08-28 Wim Michiels , Bin Zhou

A High Performance Computing alternative to traditional Krylov subspace methods, pipelined Krylov subspace solvers offer better scalability in the strong scaling limit compared to standard Krylov subspace methods for large and sparse linear…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-25 Siegfried Cools , Wim Vanroose

Hardware trends have motivated the development of mixed precision algo-rithms in numerical linear algebra, which aim to decrease runtime while maintaining acceptable accuracy. One recent development is the development of an adaptive…

Numerical Analysis · Mathematics 2023-07-11 Noaman Khan , Erin Carson

Solving initial value problems and boundary value problems of Linear Ordinary Differential Equations (ODEs) plays an important role in many applications. There are various numerical methods and solvers to obtain approximate solutions…

Numerical Analysis · Mathematics 2018-05-22 Wenqiang Yang , Wenyuan Wu , Robert M. Corless

We present a high-order spacetime numerical method for discretizing and solving linear initial-boundary value problems using wavelet-based techniques with user-prescribed error estimates. The spacetime wavelet discretization yields a system…

Numerical Analysis · Mathematics 2025-09-04 Cody D. Cochran , Karel Matous

We prove existence of positive solutions to a boundary value problem depending on discrete fractional operators. Then, corresponding discrete fractional Lyapunov-type inequalities are obtained.

Classical Analysis and ODEs · Mathematics 2017-10-13 Amar Chidouh , Delfim F. M. Torres

In numerous applications the mathematical model consists of different processes coupled across a lower dimensional manifold. Due to the multiscale coupling, finite element discretization of such models presents a challenge. Assuming that…

Numerical Analysis · Mathematics 2019-12-20 Miroslav Kuchta

Krylov complexity provides a powerful framework for characterizing the dynamical evolution of quantum systems through the spreading of states in Krylov space. The motivation for this is rooted in the optimality of the Krylov basis for the…

Quantum Physics · Physics 2026-03-10 Saud Čindrak , Kathy Lüdge

In this technical note, we are concerned with the problem of solving variational inequalities with improved convergence rates. Motivated by Nesterov's accelerated gradient method for convex optimization, we propose a Nesterov's accelerated…

Optimization and Control · Mathematics 2022-12-21 Shaolin Tan , Jinhu Lu