We build an analytical model for an application utilizing master-slave paradigm. In the model, only three architecture parameters are used: latency, bandwidth and flop rate. Instea...
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
We consider the problem of learning in multilayer feed-forward networks of linear threshold units. We show that the Vapnik-Chervonenkis dimension of the class of functions that ca...
Some classes of real-time systems function in environments which cannot be modeled with static approaches. In such environments, the arrival rates of events which drive transient ...
Lonnie R. Welch, Binoy Ravindran, Paul V. Werme, M...
Multi-task learning aims at combining information across tasks to boost prediction performance, especially when the number of training samples is small and the number of predictor...