- Patent Title: Continual neural network learning via explicit structure learning
-
Application No.: US16176419Application Date: 2018-10-31
-
Publication No.: US11645509B2Publication Date: 2023-05-09
- Inventor: Yingbo Zhou , Xilai Li , Caiming Xiong
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: Salesforce.com, Inc.
- Current Assignee: Salesforce.com, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Haynes and Boone, LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
Embodiments for training a neural network using sequential tasks are provided. A plurality of sequential tasks are received. For each task in the plurality of tasks a copy of the neural network that includes a plurality of layers is generated. From the copy of the neural network a task specific neural network is generated by performing an architectural search on the plurality of layers in the copy of the neural network. The architectural search identifies a plurality of candidate choices in the layers of the task specific neural network. Parameters in the task specific neural network that correspond to the plurality of candidate choices and that maximize architectural weights at each layer are identified. The parameters are retrained and merged with the neural network. The neural network trained on the plurality of sequential tasks is a trained neural network.
Information query