Skip to main content
King Abdullah University of Science and Technology
Scientific Computing and Machine Learning
SCML
Scientific Computing and Machine Learning
Main navigation
  • Home
  • People
    • Principal Investigators
    • Research Scientists
    • Postdoctoral Fellows
    • Students
    • All Profiles
  • Events
    • All Events
    • Events Calendar
  • News
  • KAUST Innovation Hub in Shenzhen
  • Opportunities

convex optimization

Additive Schwarz Methods for Convex Optimization - Theory and Applications

Jongho Park, Research Scientist, Applied Mathematics and Computational Sciences
Sep 19, 16:00 - 17:00

B5 L5 R5209

Additive Schwarz methods convex optimization

This talk is devoted to additive Schwarz methods for convex optimization. First, we propose an abstract framework for additive Schwarz methods for convex optimization. The framework's flexibility allows it to handle composite optimization problems and inexact local solvers. Moreover, it establishes a sharp convergence theory that agrees with the classical theory when addressing linear problems.

Scientific Computing and Machine Learning (SCML)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2024 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice