Optimal resource scheduling in multiagent systems is a computationally challenging task, particularly when the values of resources are not additive. We consider the combinatorial ...
Dmitri A. Dolgov, Michael R. James, Michael E. Sam...
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matchi...
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...