privacy amplification

Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy NeurIPS 2022 Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging NeurIPS 2022 Privacy Amplification by Decentralization AISTATS 2022 Privacy Amplification by Subsampling in Time Domain AISTATS 2022 Privacy Amplification via Shuffling for Linear Contextual Bandits ALT 2022 Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss NeurIPS 2022 Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning NeurIPS 2022 FLAME: Differentially Private Federated Learning in the Shuffle Model AAAI 2021 Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning NeurIPS 2021 Privacy Amplification via Random Check-Ins NeurIPS 2020 Variational Bayes in Private Settings (VIPS) (Extended Abstract) IJCAI 2020 Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases NeurIPS 2019 Oblivious Sampling Algorithms for Private Data Analysis NeurIPS 2019 Poission Subsampled Rényi Differential Privacy ICML 2019 Privacy Amplification by Mixing and Diffusion Mechanisms NeurIPS 2019 Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences NeurIPS 2018