There is a need for information, application, and other enterprise architectures which are robust and flexible enough to meet the challenges of today’s heterogeneous, rapidly cha...
We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Although the diversity of platforms for network experimentation is a boon to the development of protocols and distributed systems, it is challenging to exploit its benefits. Impl...
— The rapid growth in the popularity of cellular networks has led to aggressive deployment and a rapid expansion of services. Services based on the integration of these networks ...
Mike P. Wittie, Brett Stone-Gross, Kevin C. Almero...
Abstract. This paper introduces the notion of the variadic neural network (VNN). The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n ...