The integration of immersive coding for privacy in machine learning provides an innovative approach to safeguarding sensitive data, enhancing security without sacrificing model performance.
While existing privacy-preserving techniques like Secure Multiparty Computation and Homomorphic Encryption have shown effectiveness, they frequently compromise ML model efficiency and performance.
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