2019
Efficient Deep Approximation of GMMs
NeurIPS 2019poster
The universal approximation theorem states that any regular function can be approximated closely using a single hidden layer neural network. Some recent work has shown that, for some special functions, the number of nodes in such an approximation could be exponentially reduced with multi-layer neura…