Asymptotic convergence of spectral inverse iterations for stochastic eigenvalue problems
Sign Up to like & getrecommendations! Published in 2019 at "Numerische Mathematik"
DOI: 10.1007/s00211-019-01034-w
Abstract: We consider and analyze applying a spectral inverse iteration algorithm and its subspace iteration variant for computing eigenpairs of an elliptic operator with random coefficients. With these iterative algorithms the solution is sought from a… read more here.
Keywords: asymptotic convergence; space; convergence spectral; eigenvalue ... See more keywords
A partially inexact ADMM with o(1/n) asymptotic convergence rate, ????(1/n) complexity, and immediate relative error tolerance
Sign Up to like & getrecommendations! Published in 2020 at "Optimization"
DOI: 10.1080/02331934.2020.1772255
Abstract: In this work, we propose a new partially inexact Alternating Direction Method of Multipliers (ADMM) with relative error tolerance. This method departs from previous semi-inexact variants of the ADMM by allowing the second subproblem to… read more here.
Keywords: asymptotic convergence; error tolerance; relative error; error ... See more keywords
Non-asymptotic convergence analysis of inexact gradient methods for machine learning without strong convexity
Sign Up to like & getrecommendations! Published in 2017 at "Optimization Methods and Software"
DOI: 10.1080/10556788.2017.1296439
Abstract: Many recent applications in machine learning and data fitting call for the algorithmic solution of structured smooth convex optimization problems. Although the gradient descent method is a natural choice for this task, it requires exact… read more here.
Keywords: asymptotic convergence; machine learning; method; non asymptotic ... See more keywords