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

Neural Information Processing Systems 

Summary This paper concerns the asynchronous sparse online and stochastic optimization settings. In this setting several algorithms work in parallel to optimize the same objective. The difficulty herein lies that not all algorithms are aware of the current state of the objective, complicating the analysis. Existing convergence guarantees in this setting only hold for box shaped constraint sets. In this paper the authors develop several new algorithms that can deal with non-box shaped constrained sets: "AsynCADA" and "HedgeHog!".