… method, however, where the first and second distribution moments at each stage are … is
undermined by aggregated information loss from layer to layer. This information loss can affect …

… information effectively because it only adopts a fixed stride strategy, which may result in poor
generalization ability and information loss… in the down-sampling layers during the training …

… They are problems in that we are trying to retrieve information about an entire utterance
rather than … describing the distribution of the given input data sequence with variable-length. …

… and also a heavy-tailed distribution (GE + heavy-tailed) to model the losses is able to present
… using another probability distribution, as we propose in this new packet loss model, which …

… In this paper we propose a Gaussian Mixture loss (GM loss) … a Gaussian Mixture (GM)
distribution, with each component … with 6 convolution layers and a fully connected layer with a …

… In the case that DisturbLabel provides strong regularization, eg, in the case of ImageNet
training where the wrong label is distributed over all the 1000 categories, we will slightly …

… Information measure for the layer-wise analysis. With such measure, we demonstrate that
information loss is … of hidden layers as a parametric implicit distribution, we propose a Fisher …

… same layer need to be evaluated before passing information to … distribution loss is introduced
for calculating the information … to design our method for handling information loss in SNNs. …

… We assume that H(X) > 0 and suppose we have a class of conditional distributions Q from
which to search for a variable U meant to approximate X (eg, the hidden layer in our neural …

… loss only considered errors in the physical layer. At the physical layer, the main causes of
packet loss … Russ and Haghani [141] presented a distribution of consecutive packet losses as a …