privacy-utility trade-off

PrivECG: generating private ECG for end-to-end anonymization MLHC 2023 Protecting Global Properties of Datasets with Distribution Privacy Mechanisms AISTATS 2023 Towards a Framework for Privacy-Preserving Pedestrian Analysis WACV 2023 Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints NeurIPS 2022 Improved Utility Analysis of Private CountSketch NeurIPS 2022 Post-processing of Differentially Private Data: A Fairness Perspective IJCAI 2022 Privacy Amplification by Decentralization AISTATS 2022 SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression NeurIPS 2022 DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for Deep Neural Networks CVPR 2021 Locally Differentially-Private Randomized Response for Discrete Distribution Learning JMLR 2021 Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation With Manipulable Semantics CVPR 2021 Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential Privacy AISTATS 2020 Utility/Privacy Trade-off through the lens of Optimal Transport AISTATS 2020 Differentially Private Anonymized Histograms NeurIPS 2019 Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images CVPR 2018 Preserving Privacy of Continuous High-dimensional Data with Minimax Filters AISTATS 2015 Extremal Mechanisms for Local Differential Privacy NeurIPS 2014 Near-optimal Differentially Private Principal Components NeurIPS 2012 Privacy Aware Learning NeurIPS 2012