Corpus ID: 220265581

Training highly effective connectivities within neural networks with randomly initialized, fixed weights

  title={Training highly effective connectivities within neural networks with randomly initialized, fixed weights},
  author={Cristian Ivan and R. 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 hyperparameters defining cutoff thresholds and therefore remove the need for iteratively searching optimal values of such hyperparameters. We can achieve similar or higher performances than in the case of training all weights, with a similar computational cost as for standard training techniques. Besides switching… Expand
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