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Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement
In this paper we propose to use HyperNetworks to break the fixed ratio of FLOPs to parameters of standard convolutions.
Rounding Methods for Neural Networks with Low Resolution Synaptic Weights
We further use these methods to investigate the performance of three common neural network algorithms under fixed memory size of the weight matrix with different weight resolutions.
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