gaussian mechanism

Approximate Differential Privacy of the ℓ_2 Mechanism ICML 2025 Dyn-D^2P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee IJCAI 2025 Private Lossless Multiple Release ICML 2025 Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions ICLR 2025 One-shot Empirical Privacy Estimation for Federated Learning ICLR 2024 Revisiting Differentially Private ReLU Regression NeurIPS 2024 The Relative Gaussian Mechanism and its Application to Private Gradient Descent AISTATS 2024 Universal Exact Compression of Differentially Private Mechanisms NeurIPS 2024 A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning NeurIPS 2023 Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks AAAI 2023 Individual Privacy Accounting with Gaussian Differential Privacy ICLR 2023 Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations COLT 2023 Protecting Global Properties of Datasets with Distribution Privacy Mechanisms AISTATS 2023 Smooth Flipping Probability for Differential Private Sign Random Projection Methods NeurIPS 2023 A bounded-noise mechanism for differential privacy COLT 2022 Differentially private multi-party data release for linear regression UAI 2022 Differential privacy for symmetric log-concave mechanisms AISTATS 2022 Improved Utility Analysis of Private CountSketch NeurIPS 2022 Kantorovich Mechanism for Pufferfish Privacy AISTATS 2022 Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy NeurIPS 2022 Optimal Algorithms for Mean Estimation under Local Differential Privacy ICML 2022 Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NeurIPS 2022 Subspace Differential Privacy AAAI 2022 A Central Limit Theorem for Differentially Private Query Answering NeurIPS 2021 Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics ALT 2021