no code implementations • NeurIPS 2015 • Kent Quanrud, Daniel Khashabi
We study the performance of standard online learning algorithms when the feedback is delayed by an adversary.
no code implementations • 20 May 2016 • Daniel Khashabi, Kent Quanrud, Amirhossein Taghvaei
We consider the problem of strongly-convex online optimization in presence of adversarial delays; in a T-iteration online game, the feedback of the player's query at time t is arbitrarily delayed by an adversary for d_t rounds and delivered before the game ends, at iteration t+d_t-1.
