We consider discrete infinite-state Markov chains which contain an eager finite attractor. A finite attractor is a finite subset of states that is eventually reached with prob...
Parosh Aziz Abdulla, Noomene Ben Henda, Richard Ma...
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
Task-selection policies are critical to the performance of any architecture that uses speculation to extract parallel tasks from a sequential thread. This paper demonstrates that ...
Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam...
In a distributed heterogeneous computing system, the resources have different capabilities and tasks have different requirements. To maximize the performance of the system, it is ...
Jong-Kook Kim, Sameer Shivle, Howard Jay Siegel, A...
The problem of task assignment in heterogeneous computing systems has been studied for many years with many variations. We have developed a new hybrid approximation algorithm. The...