Abstract
In this paper, we study constrained online convex optimization (OCO) in the presence of feedback delays. The loss/constraint functions vary with time and their feedback information is revealed to the decision maker with delays, which arise naturally in many applications due to the latency associated with computation and communication. The effects of delays are not captured by standard OCO, where feedback information is disclosed to the decision maker immediately after a decision is made. We develop a modified online saddle point algorithm for constrained OCO with feedback delays. Sublinear regret and sublinear constraint violation bounds are established for the proposed algorithm and the impact of delays on the performance of the algorithm is highlighted.
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