Stochastic Hamiltonian Gradient Methods for Smooth Games

ICML 2020 Nicolas LoizouHugo BerardAlexia Jolicoeur-MartineauPascal VincentSimon Lacoste-JulienIoannis Mitliagkas

The success of adversarial formulations in machine learning has brought renewed motivation for smooth games. In this work, we focus on the class of stochastic Hamiltonian methods and provide the first convergence guarantees for certain classes of stochastic smooth games... (read more)

PDF Abstract ICML 2020 PDF

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet