Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
This paper addresses the problem of extending the lifetime of a batterypowered mobile host in a client-server wireless network by using task migration and remote processing. This ...
In this paper, we establish a theoretical framework for a new concept of scheduling called soft scheduling. In contrasts to the traditional schedulers referred as hard schedulers,...
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...