conftrace_

differential privacy

1,207 papers

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Also known as

DP

Co-occurring keywords · papers mentioning both

federated learning (146) stochastic gradient descent (72) sample complexity (68) regret bound (53) privacy-preserving learning (49) privacy preservation (47) privacy-preserving machine learning (43) privacy-utility trade-off (42) synthetic data (37) large language model (36)

Papers

Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting EMNLP 2024 Thompson Sampling Itself is Differentially Private AISTATS 2024 To Share or Not to Share: What Risks Would Laypeople Accept to Give Sensitive Data to Differentially-Private NLP Systems? COLING 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy ICLR 2024 Truthful High Dimensional Sparse Linear Regression NeurIPS 2024 Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification NeurIPS 2024 Universal Exact Compression of Differentially Private Mechanisms NeurIPS 2024 Universally Instance-Optimal Mechanisms for Private Statistical Estimation COLT 2024 Unveiling Privacy, Memorization, and Input Curvature Links ICML 2024 User Inference Attacks on Large Language Models EMNLP 2024 User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates AISTATS 2024 ViP: A Differentially Private Foundation Model for Computer Vision ICML 2024 Wasserstein Differential Privacy AAAI 2024 k-Means Clustering with Distance-Based Privacy NeurIPS 2023 A Customized Text Sanitization Mechanism with Differential Privacy ACL 2023 Adaptive Data Analysis in a Balanced Adversarial Model NeurIPS 2023 Adaptive False Discovery Rate Control with Privacy Guarantee JMLR 2023 Adaptive Privacy Composition for Accuracy-first Mechanisms NeurIPS 2023 Adversarially Robust Distributed Count Tracking via Partial Differential Privacy NeurIPS 2023 Algorithmically Effective Differentially Private Synthetic Data COLT 2023 Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler COLT 2023 Algorithms for bounding contribution for histogram estimation under user-level privacy ICML 2023 (Amplified) Banded Matrix Factorization: A unified approach to private training NeurIPS 2023 Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano ICML 2023