公开(公告)号：US20220019856A1

公开(公告)日：2022-01-20

申请号：US17377142

申请日：2021-07-15

Applicant: Google LLC

Inventor： Jaehoon Lee ,  Daiyi Peng ,  Yuan Cao ,  Jascha Narain Sohl-Dickstein ,  Daniel Sung-Joon Park

IPC: G06K9/62 ,  G06N3/08

Abstract: A method for predicting performance of a neural network (NN) is described. The method includes receiving a training data set having a set of training samples; receiving a validation data set having a set of validation pairs; initializing (i) a validation-training kernel matrix representing similarities of the validation inputs in the validation data set and the training inputs in the training data set and (ii) a training-training kernel matrix representing similarities across the training inputs within the training data set; generating a final updated validation-training kernel matrix and a final updated training-training kernel matrix; performing the following operations at least once: generating predicted validation outputs for the validation inputs, and updating an accuracy score of the NN based on the predicted validation outputs and the validation outputs; and outputting the updated accuracy score as a final accuracy score representing performance of the NN.