Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
The continuing trend toward greater processing power, larger storage, and in particular increased display surface by using multiple monitor supports increased multi-tasking by the...
Dugald Ralph Hutchings, Greg Smith, Brian Meyers, ...
Until now, system administrators have lacked a flexible real-time network traffic flow monitoring package. Such a package must provide a wide range of services but remain flexible ...
David Moore, Ken Keys, Ryan Koga, Edouard Lagache,...
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...