In the online linear optimization problem, a learner must choose, in each round, a decision from a set D ⊂ Rn in order to minimize an (unknown and changing) linear cost function...
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
We study a class of generalized bundle methods for which the stabilizing term can be any closed convex function satisfying certain properties. This setting covers several algorithm...
StaticPSM (Power-Saving Mode)schemes employed in the current IEEE 802.11 implementations could not provide any delag-performance guarantee because of their fixed wakeup intervals. ...
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon