We consider stochastic impulse control problems where the process is driven by one-dimensional diffusions. Impulse control problems are widely applied to financial engineering and...
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...
Recently several authors have proposed stochastic models of the growth of the Web graph that give rise to power-law distributions. These models are based on the notion of preferen...
Mark Levene, Trevor I. Fenner, George Loizou, Rich...
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
Abstract--This research investigates the problem of robust dynamic resource allocation for heterogeneous distributed computing systems operating under imposed constraints. Often, s...
Jay Smith, Edwin K. P. Chong, Anthony A. Maciejews...