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Faster Multiplication Triplet Generation from Homomorphic Encryption for Practical Privacy-Preserving Machine Learning under a Narrow Bandwidth
Privacy-preserving Machine Learning Secure Two-party Computation Applied Crypto
2018/2/8
Machine learning algorithms are used by more and more online applications to improve the services. Machine learning-based online services are usually accessed by thousands of clients concurrently thro...
SecureML: A System for Scalable Privacy-Preserving Machine Learning
Privacy-preserving machine learning secure computation
2017/5/11
Machine learning is widely used in practice to produce predictive models for applications such as image processing, speech and text recognition. These models are more accurate when trained on large am...
Practical Secure Aggregation for Privacy Preserving Machine Learning
Privacy Preserving Machine Learning cryptographic protocols
2017/3/31
We design a novel, communication-efficient, failure-robust protocol for secure aggregation of high-dimensional data. Our protocol allows a server to compute the sum of large, user-held data vectors fr...