Adaptive Algorithms for Online Optimization
The online learning framework captures a wide variety of learning problems. The setting is as follows - in each round, we have to choose a point from some fixed convex domain. Then, we are presented a convex loss function, according to which we incur a loss. The loss over T rounds is simply the sum of all the losses. The aim of most online learning algorithm is to minimize *regret* : the differ...