An End-to-End System for Efficient Multiparty Computation in Privacy-Preserving Machine Learning
The proposed Secure Multiparty Computation protocol enables collaborative training of linear and logistic regression models while providing formal privacy guarantees for participant data, and adapts the iterative gradient descent algorithm to operate securely over secretly shared vectors.
Michael Leon, Putra Widhi, R. Munir
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