Invention Grant
- Patent Title: Per kernel Kmeans compression for neural networks
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Application No.: US15702193Application Date: 2017-09-12
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Publication No.: US11055604B2Publication Date: 2021-07-06
- Inventor: Yonatan Glesner , Gal Novik , Dmitri Vainbrand , Gal Leibovich
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Jaffery Watson Mendosa & Hamilton LLP
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06F3/06

Abstract:
Methods and apparatus relating to techniques for incremental network quantization. In an example, an apparatus comprises logic, at least partially comprising hardware logic to determine a plurality of weights for a layer of a convolutional neural network (CNN) comprising a plurality of kernels; organize the plurality of weights into a plurality of clusters for the plurality of kernels; and apply a K-means compression algorithm to each of the plurality of clusters. Other embodiments are also disclosed and claimed.
Public/Granted literature
- US20190080222A1 PER KERNEL KMEANS COMPRESSION FOR NEURAL NETWORKS Public/Granted day:2019-03-14
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