Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond

Online learning algorithms are designed to solve prediction and learning problems for streaming data or batch data whose volume is too large to be processed all at once. Applications include online routing [1], online auctions [2], online classification and regression [3], as well as online resource allocation [4].