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cs.LG2022
Bit-wise Training of Neural Network Weights
Cristian Ivan
We introduce an algorithm where the individual bits representing the weights of a neural network are learned. This method allows training weights with integer values on arbitrary b…
cs.LG2020
Training highly effective connectivities within neural networks with randomly initialized, fixed weights
Cristian Ivan, Razvan Florian
We present some novel, straightforward methods for training the connection graph of a randomly initialized neural network without training the weights. These methods do not use hyp…