: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Latency has become an important metric for network monitoring since the emergence of new latency-sensitive applications (e.g., algorithmic trading and high-performance computing)....
Myungjin Lee, Nick G. Duffield, Ramana Rao Kompell...
We examine the problem of evaluating selection queries over imprecisely represented objects. Such objects are used either because they are much smaller in size than the precise on...
We present a dynamic voltage scaling (DVS) technique that minimizes system-wide energy consumption for both periodic and sporadic tasks. It is known that a system consists of proc...
In this paper, we initiate the study of designing approximation algorithms for FaultTolerant Group-Steiner (FTGS) problems. The motivation is to protect the well-studied group-Ste...