Investigating the Compositional Structure Of Deep Neural Networks

17 Feb 2020Francesco CraigheroFabrizio AngaroniAlex GraudenziFabio StellaMarco Antoniotti

The current understanding of deep neural networks can only partially explain how input structure, network parameters and optimization algorithms jointly contribute to achieve the strong generalization power that is typically observed in many real-world applications. In order to improve the comprehension and interpretability of deep neural networks, we here introduce a novel theoretical framework based on the compositional structure of piecewise linear activation functions... (read more)

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