Invention Grant
- Patent Title: Black-box optimization using neural networks
-
Application No.: US16601505Application Date: 2019-10-14
-
Publication No.: US11354594B2Publication Date: 2022-06-07
- Inventor: Yutian Chen , Joao Ferdinando Gomes de Freitas
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06N3/04 ; G06N3/08 ; G06F17/18

Abstract:
Methods and systems for determining an optimized setting for one or more process parameters of a machine learning training process are described. One of the methods includes processing a current network input using a recurrent neural network in accordance with first values of the network parameters to obtain a current network output, obtaining a measure of the performance of the machine learning training process with an updated setting defined by the current network output, and generating a new network input that includes (i) the updated setting defined by the current network output and (ii) the measure of the performance of the training process with the updated setting defined by the current network output.
Public/Granted literature
- US20200042901A1 BLACK-BOX OPTIMIZATION USING NEURAL NETWORKS Public/Granted day:2020-02-06
Information query