GitHub

A Python demonstration of speeding up matrix multiplication and reducing memory using a quantum-inspired low-rank SVD trick, with examples in AI.

This repository demonstrates a powerful, classical linear algebra technique—low-rank approximation via Singular Value Decomposition (SVD)—to dramatically accelerate common matrix operations like GEMM ...
GitHub

Invicta33/cuopt-examples_OV

NVIDIA cuOpt is a GPU-accelerated combinatorial and linear optimization engine for solving complex route optimization problems such as Vehicle Routing and large Linear Programming problems. This ...
JSTOR Daily

ON THE OPTIMIZATION OF EXTRAPOLATION METHODS FOR SINGULAR LINEAR SYSTEMS

Journal of Computational Mathematics, Vol. 26, No. 2 (March 2008), pp. 227-239 (13 pages) We discuss semiconvergence of the extrapolated iterative methods for solving singular linear systems. We ...
JSTOR Daily

ON BLOCK PRECONDITIONERS FOR PDE-CONSTRAINED OPTIMIZATION PROBLEMS

Recently, Bai proposed a block-counter-diagonal and a block-counter-triangular preconditioning matrices to precondition the GMRES method for solving the structured system of linear equations arising ...
IEEE

Enhanced Control of Nonlinear Cyber-Physical Systems: A Higher-Order Relaxation Matrix-Based Convex Optimization Algorithm

Abstract: This paper investigates the static output feedback (SOF) control problem of T-S fuzzy systems based on higher-order Lyapunov functions (HO-LFs). Firstly, to alleviate the conservatism of ...
SciELO

A Heuristic Algorithm Based on Line-up Competition and Generalized Pattern Search for Solving Integer and Mixed Integer Non-linear Optimization Problems

The global optimization of integer and mixed integer non-linear problems has a lot of applications in engineering. In this paper a heuristic algorithm is developed using line-up competition and ...