Invention Grant
- Patent Title: Method and apparatus for learning low-precision neural network that combines weight quantization and activation quantization
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Application No.: US15914229Application Date: 2018-03-07
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Publication No.: US11270187B2Publication Date: 2022-03-08
- Inventor: Yoo Jin Choi , Mostafa El-Khamy , Jungwon Lee
- Applicant: Samsung Electronics Co., Ltd.
- Applicant Address: KR Gyeonggi-do
- Assignee: Samsung Electronics Co., Ltd.
- Current Assignee: Samsung Electronics Co., Ltd.
- Current Assignee Address: KR Gyeonggi-do
- Agency: The Farrell Law Firm, P.C.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08

Abstract:
A method is provided. The method includes selecting a neural network model, wherein the neural network model includes a plurality of layers, and wherein each of the plurality of layers includes weights and activations; modifying the neural network model by inserting a plurality of quantization layers within the neural network model; associating a cost function with the modified neural network model, wherein the cost function includes a first coefficient corresponding to a first regularization term, and wherein an initial value of the first coefficient is pre-defined; and training the modified neural network model to generate quantized weights for a layer by increasing the first coefficient until all weights are quantized and the first coefficient satisfies a pre-defined threshold, further including optimizing a weight scaling factor for the quantized weights and an activation scaling factor for quantized activations, and wherein the quantized weights are quantized using the optimized weight scaling factor.
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