Safeguarded Learned Convex Optimization

TL; DR - Safeguarded learning to optimize (L2O) algorithms can leverage the strength of machine learning tools while maintaining convergence guarantees.

less than 1 minute read

Preprint Citation Code Slides

Howard Heaton, Xiaohan Chen, Atlas Wang, and Wotao Yin

(Under Construction - Jan 2021)

Share on

Twitter Reddit LinkedIn

MiniMax L2O: A Pilot Study

less than 1 minute read

TL; DR - We introduce the learning to optimize (L2O) methodology to the minimax problems for the first time.

Projecting to Manifolds via Unsupervised Learning

10 minute read

TL; DR - We present an algorithm for performing projections onto the low dimensional manifolds that efficiently represent true data.

Async Inertial Method for Common Fixed Points

less than 1 minute read

TL; DR - Baby version of ARock for common fixed points without using any probability.