Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Meta-modelling is at the core of Model-Driven Engineering, where it is used for language engineering and domain modelling. The OMG’s Meta-Object Facility is the standard framewor...
— This paper introduces a simple analytical model for estimating standby and switching power dissipation in deep submicron CMOS digital circuits. The model is based on Berkeley S...
Abstract—In this paper, we introduce FlowSifter, a systematic framework for online application protocol field extraction. FlowSifter introduces a new grammar model Counting Regu...
Chad R. Meiners, Eric Norige, Alex X. Liu, Eric To...