A significant portion of the population is at risk of being excluded from online learning environments. People with learning and/or physically disabilities may be prevented from p...
This paper describes a general framework for converting online game playing algorithms into constrained convex optimization algorithms. This framework allows us to convert the wel...
In prediction with expert advice the goal is to design online prediction algorithms that achieve small regret (additional loss on the whole data) compared to a reference scheme. I...
We consider on-line scheduling of unit time jobs on a single machine with job-dependent penalties. The jobs arrive on-line (one by one) and can be either accepted and scheduled, o...
We present a new class of perceptron-like algorithms with margin in which the "effective" learning rate, defined as the ratio of the learning rate to the length of the we...