Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

The optimization of architecture of feed-forward neural networks is a complex task of high importance in supervised learning because it has a great impact on the convergence of learning methods. In ...

Deep Recurrent Neural Network (DRNN) is an effective deep learning method with a wide variety of applications. Manually designing the architecture of a DRNN for any specific task requires expert ...