Invention Application
- Patent Title: MULTIPLICATION-FREE APPROXIMATION FOR NEURAL NETWORKS AND SPARSE CODING
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Application No.: US16306736Application Date: 2016-06-29
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Publication No.: US20190130148A1Publication Date: 2019-05-02
- Inventor: Gautham Chinya , Shihao Ji , Arnab Paul
- Applicant: Intel Corporation
- International Application: PCT/US2016/039977 WO 20160629
- Main IPC: G06K7/10
- IPC: G06K7/10 ; G06F17/16 ; G06N20/10 ; G06N3/04 ; G06K7/14

Abstract:
Systems, apparatuses and methods may provide for replacing floating point matrix multiplication operations with an approximation algorithm or computation in applications that involve sparse codes and neural networks. The system may replace floating point matrix multiplication operations in sparse code applications and neural network applications with an approximation computation that applies an equivalent number of addition and/or subtraction operations.
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