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Deep and Modular Neural Netwoks
ABSTRACT
In this chapter, we focus on two important areas in neural computation, i.e., deep and modular neural networks,
given the fact that both deep and modular neural networks have been among the most powerful machine learning and
pattern recognition techniques for complex AI problem solving. We begin by providing a general overview of deep
and modular neural networks to describe the general motivation behind such neural architectures and requirements
for complex problem solving. Next, we describe background and motivation, methodologies, major building blocks,
and the state-of-the-art hybrid learning strategy in context of deep neural architectures. Then, we describe
background and motivation, taxonomy and learning algorithms pertaining to various yet typical modular neural
network architectures. Furthermore, we also examine relevant issues and discuss open problems in deep and
modular neural network areas.
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