Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks

Jason Kuen, Xiangfei Kong, Zhe Lin +4

It is desirable to train convolutional networks (CNNs) to run more efficiently during inference. In many cases however, the computational budget that the system has for inference c…