Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging

NeurIPS 2019 Pooria JoulaniAndrás GyörgyCsaba Szepesvari

We present two new algorithms, ASYNCADA and HEDGEHOG, for asynchronous sparse online and stochastic optimization. ASYNCADA is, to our knowledge, the first asynchronous stochastic optimization algorithm with finite-time data-dependent convergence guarantees for generic convex constraints... (read more)

PDF Abstract


No code implementations yet. Submit your code now

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.