We consider the problem of minimizing average flow time on multiple machines when each job can be assigned only to a specified subset of the machines. This is a special case of sc...
Motivated by applications in grid computing and projects management, we study multiprocessor scheduling in scenarios where there is uncertainty in the successful execution of jobs...
In two-class score-based problems the combination of scores from an ensemble of experts is generally used to obtain distributions for positive and negative patterns that exhibit a ...
Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been ...
We present a novel approach to solving Quantified Boolean Formulas (QBF) that combines a search-based QBF solver with machine learning techniques. We show how classification met...