This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Modeling and predicting of mental workload are among the most important issues in studying human performance in complex systems. Ample research has shown that the amplitude of the ...
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
— This paper introduces a buffer occupancy -based admission control mechanism aimed to counter link congestion while fairly sharing the bandwidth in converged IP and broadcasting...
Yassine Hadjadj Aoul, Abdelhamid Nafaa, Ahmed Meha...
Computationally complex and data intensive atomic scale biomolecular simulation is enabled via Processing in Network Storage (PINS): a novel distributed system framework to overco...
Paul Brenner, Justin M. Wozniak, Douglas Thain, Aa...