Invention Application
- Patent Title: OPTIMIZATION USING LEARNED NEURAL NETWORK OPTIMIZERS
-
Application No.: US17665457Application Date: 2022-02-04
-
Publication No.: US20220253704A1Publication Date: 2022-08-11
- Inventor: Ekin Dogus Cubuk , Luke Shekerjian Metz , Samuel Stern Schoenholz , Amil A. Merchant
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Main IPC: G06N3/08
- IPC: G06N3/08

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing optimization using an optimizer neural network. One of the methods includes for each optimizer network parameter, randomly sampling a perturbation value; generating a plurality of sets of candidate values for the optimizer network parameters, for each set of candidate values of the optimizer network parameters: determining a respective loss value representing a performance of the optimizer neural network in updating one or more sets of inner parameters in accordance with the set of candidate of values of the optimizer network parameters; and updating the current values of the optimizer network parameters based on the loss values for the plurality of sets of candidate values of the optimizer network parameters.
Information query