Invention Grant
- Patent Title: Quantization of neural network parameters
-
Application No.: US15851258Application Date: 2017-12-21
-
Publication No.: US11138505B2Publication Date: 2021-10-05
- Inventor: Masaya Kibune , Xuan Tan
- Applicant: FUJITSU LIMITED
- Applicant Address: JP Kawasaki
- Assignee: FUJITSU LIMITED
- Current Assignee: FUJITSU LIMITED
- Current Assignee Address: JP Kawasaki
- Agency: Maschoff Brennan
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04 ; G06N3/063

Abstract:
A method of generating a neural network may be provided. A method may include applying non-linear quantization to a plurality of synaptic weights of a neural network model. The method may further include training the neural network model. Further, the method ma include generating a neural network output from the trained neural network model based on or more inputs received by the trained neural network model.
Public/Granted literature
- US20190197408A1 QUANTIZATION OF NEURAL NETWORK PARAMETERS Public/Granted day:2019-06-27
Information query