Private Nearest Neighbors Classification in Federated Databases

By Phillipp Schoppmann, Adrià Gascón, Borja Balle. 2018

16 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Ali Shahin Shamsabadi
2. Nitin Agrawal
3. Matt J. Kusner
4. Adrià Gascón
5. Yang Liu
6. Silvia Chiappa
7. Sergey I. Nikolenko
8. Peter Kairouz

Citations in the corpus

• QUOTIENT: Two-Party Secure Neural Network Training and Prediction (2019, methodology): “These trade-offs lead to a natural idea recently exploited in several works in the secure computation for ML: one should design protocols that are customized to full algorithms, such as the training of linear/logistic regressors and DNNs [14, 41, 44], matrix factorization [43], or k-nearest neighbor”