Samsung electronics co., ltd. (20240211738). APPARATUS AND METHOD WITH ENCRYPTED DATA NEURAL NETWORK OPERATION simplified abstract
Contents
APPARATUS AND METHOD WITH ENCRYPTED DATA NEURAL NETWORK OPERATION
Organization Name
Inventor(s)
APPARATUS AND METHOD WITH ENCRYPTED DATA NEURAL NETWORK OPERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240211738 titled 'APPARATUS AND METHOD WITH ENCRYPTED DATA NEURAL NETWORK OPERATION
Simplified Explanation:
This patent application describes an apparatus and method for encrypted data neural network operation. The apparatus includes processors and memories that generate a target approximate polynomial to approximate a neural network operation based on input data.
- The apparatus includes one or more processors and memories storing instructions.
- The processors generate a target approximate polynomial to approximate a neural network operation.
- The target approximate polynomial is based on a first approximate polynomial, input data parameters, and a target approximation region.
- The neural network operation result is generated using the target approximate polynomial and input data.
Key Features and Innovation:
- Use of encrypted data in neural network operation.
- Generation of target approximate polynomial for neural network operation.
- Utilization of input data parameters to determine the target approximation region.
Potential Applications:
This technology can be applied in secure data processing, artificial intelligence, machine learning, and encryption systems.
Problems Solved:
This technology addresses the challenges of secure data processing, accurate neural network operations, and encrypted data handling.
Benefits:
- Enhanced security in data processing.
- Improved accuracy in neural network operations.
- Efficient handling of encrypted data.
Commercial Applications:
Potential commercial applications include secure communication systems, data encryption software, and machine learning platforms for sensitive data processing.
Questions about Encrypted Data Neural Network Operation:
1. How does this technology improve the security of neural network operations? 2. What are the potential implications of using encrypted data in machine learning systems?
2. Another relevant generic question, with a detailed answer:
How does the generation of target approximate polynomials benefit neural network operations?
By approximating complex neural network operations with target approximate polynomials, this technology improves the efficiency and accuracy of data processing, especially in encrypted environments.
Original Abstract Submitted
an apparatus and method with encrypted data neural network operation is provided. the apparatus includes one or more processors configured to execute instructions and one or more memories storing the instructions, wherein the execution of the instructions by the one or more processors configures the one or more processors to generate a target approximate polynomial, approximating a neural network operation, of a portion of a neural network model, using a determined target approximation region, for the target approximate polynomial, based on a first approximate polynomial generated based on parameters corresponding to a generation of the first approximate polynomial, a maximum value of input data to the portion of the neural network layer, and a minimum value of the input data, and generate a neural network operation result using the target approximate polynomial and the input data.
