This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
In this paper, we derive a second order mean field theory for directed graphical probability models. By using an information theoretic argument it is shown how this can be done in...
Modern VLSI technology has changed the economic rules by which the balance between processing power, memory and communications is decided in computing systems. This will have a pr...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Across many fields involving complex computing, software systems are being augmented with workflow logging functionality. The log data can be effectively organized using declarativ...