Gumbel softmaxImportant applications such as mobile computing require reducing the computational costs of neural network inference. Ideally, applications would specify their preferred tradeoff between accuracy and speed, and the network would optimize this end-to-end, using classification error to remove ...
Many electroencephalography (EEG) applications rely on channel selection methods to remove the least informative channels, e.g., to reduce the amount of electrodes to be mounted, to decrease the computational load, or to reduce overfitting effects and improve performance. Wrapper-based channel ...
During backpropagation through the backward path, the system600may approximate the discrete decision of the gating functionality component with a continuous representation. In particular, the Gumbel-Max trick and its continuous relaxation (e.g., by using a sigmoid to account for having one neuron pe...
To support discrete actions in this problem, the Gumbel-Softmax estimator [44] is used. The output of actor network is the probability mass function (PMF) of all actions, and the action is determined by sampling from this PMF. Then, the APs change their channel bonding parameters according ...
To be specific, for the l-th layer in the m-th SCPM, the channel selection matrix 𝐶𝑆𝑀𝑚𝑙CSMlm has two columns, and the number of rows in the matrix equals the number of channels. We input the parameters of the channel selection matrix into a Gumbel softmax function, and...