%0 Journal Article %J Bulletin of the Polish Academy of Sciences: Technical Sciences %D 2018 %T Theory I: Deep networks and the curse of dimensionality %A Tomaso Poggio %A Qianli Liao %K convolutional neural networks %K deep and shallow networks %K deep learning %K function approximation %X

We review recent work characterizing the classes of functions for which deep learning can be exponentially better than shallow learning. Deep convolutional networks are a special case of these conditions, though weight sharing is not the main reason for their exponential advantage.

%B Bulletin of the Polish Academy of Sciences: Technical Sciences %V 66 %G eng %N 6