Invention Application
- Patent Title: METHODS AND APPARATUS FOR ENHANCING A BINARY WEIGHT NEURAL NETWORK USING A DEPENDENCY TREE
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Application No.: US16615097Application Date: 2018-05-23
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Publication No.: US20200167654A1Publication Date: 2020-05-28
- Inventor: Yiwen Guo , Anbang Yao , Hao Zhao , Ming Lu , Yurong CHEN
- Applicant: INTEL CORPORATION
- International Application: PCT/US2018/034088 WO 20180523
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F16/22 ; G06N5/00 ; G06N3/04

Abstract:
Methods and apparatus are disclosed for enhancing a binary weight neural network using a dependency tree. A method of enhancing a convolutional neural network (CNN) having binary weights includes constructing a tree for obtained binary tensors, the tree having a plurality of nodes beginning with a root node in each layer of the CNN. A convolution is calculated of an input feature map with an input binary tensor at the root node of the tree. A next node is searched from the root node of the tree and a convolution is calculated at the next node using a previous convolution result calculated at the root node of the tree. The searching of a next node from root node is repeated for all nodes from the root node of the tree, and a convolution is calculated at each next node using a previous convolution result.
Public/Granted literature
- US11704569B2 Methods and apparatus for enhancing a binary weight neural network using a dependency tree Public/Granted day:2023-07-18
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