公开(公告)号：US20230040793A1

公开(公告)日：2023-02-09

申请号：US17870462

申请日：2022-07-21

Applicant: Google LLC

Inventor： Avneesh Sud ,  Andrea Tagliasacchi ,  Ben Usman

IPC: G06V10/77 ,  G06N5/02 ,  G06T7/70

Abstract: Example systems perform complex optimization tasks with improved efficiency via neural meta-optimization of experts. In particular, provided is a machine learning framework in which a meta-optimization neural network can learn to fuse a collection of experts to provide a predicted solution. Specifically, the meta-optimization neural network can learn to predict the output of a complex optimization process which optimizes over outputs from the collection of experts to produce an optimized output. In such fashion, the meta-optimization neural network can, after training, be used in place of the complex optimization process to produce a synthesized solution from the experts, leading to orders of magnitude faster and computationally more efficient prediction or problem solution.