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privacy-preserving machine learning

99 papers

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Also known as

PPML

Co-occurring keywords

differential privacy (1010) federated learning (1320) large language model (12755) homomorphic encryption (55) data privacy (106) model compression (3283) privacy preservation (376) logistic regression (382) distributed learning (563) model inversion attack (33)

Papers

Differentially Private and Fair Classification via Calibrated Functional Mechanism AAAI 2020
Pairwise Learning with Differential Privacy Guarantees AAAI 2020
Privacy-Preserving Gradient Boosting Decision Trees AAAI 2020
Privacy-Preserving Gaussian Process Regression – A Modular Approach to the Application of Homomorphic Encryption AAAI 2020
Practical Federated Gradient Boosting Decision Trees AAAI 2020
Improving Sparse Vector Technique with Renyi Differential Privacy NIPS 2020
ENSEI: Efficient Secure Inference via Frequency-Domain Homomorphic Convolution for Privacy-Preserving Visual Recognition CVPR 2020
AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference NIPS 2020
Logistic Regression on Homomorphic Encrypted Data at Scale AAAI 2019
KNG: The K-Norm Gradient Mechanism NIPS 2019
How Does Knowledge of the AUC Constrain the Set of Possible Ground-Truth Labelings? AAAI 2019
Partially Encrypted Deep Learning using Functional Encryption NIPS 2019
Differential Privacy Has Disparate Impact on Model Accuracy NIPS 2019
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction IJCAI 2019
The Price of Privacy for Low-rank Factorization NIPS 2018
Differentially Private Regression with Gaussian Processes AISTATS 2018
Patient Privacy in Paralinguistic Tasks INTERSPEECH 2018
Sparse Parameter Recovery from Aggregated Data ICML 2016
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization ACML 2016
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle JMLR 2016
Differentially Private Policy Evaluation ICML 2016
Near-optimal Differentially Private Principal Components NIPS 2012
Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers NIPS 2010
Privacy-preserving logistic regression NIPS 2008