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Learning in Convolutional Neural Networks Accelerated by Transfer Entropy
According to our experiments on CNN classifiers, to achieve a reasonable computational overhead--accuracy trade-off, it is efficient to consider only the inter-neural information transfer of a random subset of the neuron pairs from the last two fully connected layers.
Information Plane Analysis Visualization in Deep Learning via Transfer Entropy
Information Plane analysis is a visualization technique used to understand the trade-off between compression and information preservation in the context of the Information Bottleneck method by plotting the amount of information in the input data against the compressed representation.
Learning in Feedforward Neural Networks Accelerated by Transfer Entropy
Our contribution is an information-theoretical method for analyzing information transfer between the nodes of feedforward neural networks.
