公开(公告)号：US20220036191A1

公开(公告)日：2022-02-03

申请号：US17298853

申请日：2019-01-10

Applicant: Google LLC

Inventor： Yair Movshovitz-Attias ,  Andrew Poon ,  Ariel Gordon ,  Elad Edwin Tzvi Eban

IPC: G06N3/08 ,  G06N20/10

Abstract: A computer-implemented method for reducing the resource consumption of a convolutional neural network can include obtaining data descriptive of the convolutional neural network. The convolutional neural network can include a plurality of convolutional layers configured to perform convolutions using a plurality of kernels that each includes a plurality of kernel elements. The method can include training, for one or more training iterations, the convolutional neural network using a loss function that includes a group sparsifying regularizer term configured to sparsify a respective subset of the kernel elements of the kernel(s); following at least one training iteration, determining, for each of the kernel(s), whether to modify such kernel to remove the respective subset of the kernel elements based at least in part on respective values of the respective subset of kernel elements; and modifying at least one of the kernel(s) to remove the respective subset of the kernel elements.