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FLUENT: A Tool for Efficient Mixed-Protocol Semi-Private Function Evaluation
In modern business to customer interactions, handling private or confidential data is
essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the …
essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the …
Truncation Untangled: Scaling Fixed-Point Arithmetic for Privacy-Preserving Machine Learning to Large Models and Datasets
Fixed point arithmetic (FPA) is essential to enable practical Privacy-Preserving Machine
Learning. When multiplying two fixed-point numbers, truncation is required to ensure that the …
Learning. When multiplying two fixed-point numbers, truncation is required to ensure that the …
PIGEON: A Framework for Private Inference of Neural Networks
Abstract Privacy-Preserving Machine Learning is one of the most relevant use cases for
Secure Multiparty Computation (MPC). While private training of large neural networks such …
Secure Multiparty Computation (MPC). While private training of large neural networks such …