- 专利标题: Learned threshold pruning for deep neural networks
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申请号: US17067233申请日: 2020-10-09
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公开(公告)号: US11704571B2公开(公告)日: 2023-07-18
- 发明人: Kambiz Azarian Yazdi , Tijmen Pieter Frederik Blankevoort , Jin Won Lee , Yash Sanjay Bhalgat
- 申请人: QUALCOMM Incorporated
- 申请人地址: US CA San Diego
- 专利权人: QUALCOMM Incorporated
- 当前专利权人: QUALCOMM Incorporated
- 当前专利权人地址: US CA San Diego
- 代理机构: Seyfarth Shaw LLP
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06N3/082 ; G06N3/04
摘要:
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.
公开/授权文献
- US20210110268A1 LEARNED THRESHOLD PRUNING FOR DEEP NEURAL NETWORKS 公开/授权日:2021-04-15
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