In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
This paper addresses the question of selecting an algorithm from a predefined set that will have the best performance on a scheduling problem instance. Our goal is to reduce the e...
It is a challenging task to accurately model the performance of a face recognition system, and to predict its individual recognition results under various environments. This paper...
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
Dynamic predication has been proposed to reduce the branch misprediction penalty due to hard-to-predict branch instructions. A recently proposed dynamic predication architecture, ...