Invention Grant
- Patent Title: Learned threshold pruning for deep neural networks
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Application No.: US17067233Application Date: 2020-10-09
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Publication No.: US11704571B2Publication Date: 2023-07-18
- Inventor: Kambiz Azarian Yazdi , Tijmen Pieter Frederik Blankevoort , Jin Won Lee , Yash Sanjay Bhalgat
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: Seyfarth Shaw LLP
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/082 ; G06N3/04

Abstract:
A method for pruning weights of an artificial neural network based on a learned threshold includes determining a pruning threshold for pruning a first set of pre-trained weights of multiple pre-trained weights based on a function of a classification loss and a regularization loss. Weights are pruned from the first set of pre-trained weights when a first value of the weight is less than the pruning threshold. A second set of pre-trained weights of the multiple pre-trained weights is fine-tuned or adjusted in response to a second value of each pre-trained weight in the second set of pre-trained weights being greater than the pruning threshold.
Public/Granted literature
- US20210110268A1 LEARNED THRESHOLD PRUNING FOR DEEP NEURAL NETWORKS Public/Granted day:2021-04-15
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