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Iraj Saniee
Efficient Deep Approximation of GMMs
Shirin Jalali, Carl Nuzman, Iraj Saniee
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 neural networks.
Efficient Deep Approximation of GMMs
Shirin Jalali, Carl Nuzman, Iraj Saniee
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 neural networks.