Learning Real and Boolean Functions: When Is Deep Better Than Shallow

We describe computational tasks - especially in vision - that correspond to compositional/hierarchical functions. While the universal approximation property holds both for hierarchical and shallow networks, we prove that deep (hierarchical) networks can approximate the class of compositional functio...

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Detalhes bibliográficos
Principais autores: Mhaskar, Hrushikesh, Liao, Qianli, Poggio, Tomaso
Formato: Technical Report
Idioma:en_US
Publicado em: Center for Brains, Minds and Machines (CBMM), arXiv 2016
Assuntos:
Acesso em linha:http://hdl.handle.net/1721.1/101635