In this paper we present a cost-effective, high bandwidth server I/O network architecture, named PaScal (Parallel and Scalable). We use the PaScal server I/O network to support da...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Network information distribution is a fundamental service for any anonymization network. Even though anonymization and information distribution about the network are two orthogona...
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...