Patent ID: 11948074
Assignee: SAMSUNG ELECTRONICS CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G  B | IPC B  G

Claim 6:
7. A processor-implemented method of training a neural network, the method comprising:
initializing a weight of a current layer of an interim neural network, a first representation bit number related to the weight, a weight quantization parameter, a second representation bit number related to an output activation map output from the current layer, and an activation quantization parameter; and
generating a trained neural network by iteratively training plural layers of the interim neural network, including:
calculating a loss based on the weight as a calculated loss, the first representation bit number, the weight quantization parameter, the second representation bit number, and the activation quantization parameter, with training data; and
training the interim neural network by updating the weight, the first representation bit number, the weight quantization parameter, the second representation bit number, and the activation quantization parameter based on the calculated loss,

wherein a first parameter is dependent on first and second thresholds derived from the output activation map, and a second parameter is dependent on the first and second thresholds, and
wherein the calculating of the loss incudes a quantizing the activation quantization parameter dependent on the first parameter and the second parameter.