conftrace_

privacy guarantee

29 papers

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Co-occurring keywords

differential privacy (1016) membership inference (114) language model (4599) mean estimation (70) stochastic gradient descent (1091) federated learning (1333) entity extraction (258) local differential privacy (73) gaussian differential privacy (7) clinical note (94)

Papers

Private Synthetic Text Generation with Diffusion Models NAACL 2025
Scalable DP-SGD: Shuffling vs. Poisson Subsampling NIPS 2024
Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains AISTATS 2024
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning NIPS 2024
Optimal Learning Policies for Differential Privacy in Multi-armed Bandits JMLR 2024
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks AAAI 2024
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning NIPS 2023
Nearly Tight Bounds For Differentially Private Multiway Cut NIPS 2023
Privacy-Aware Rejection Sampling JMLR 2023
Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023
Gaussian Membership Inference Privacy NIPS 2023
Forget Unlearning: Towards True Data-Deletion in Machine Learning ICML 2023
Unbounded Differentially Private Quantile and Maximum Estimation NIPS 2023
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy NIPS 2022
Near-Optimal Correlation Clustering with Privacy NIPS 2022
One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks EMNLP 2022
Task-level Differentially Private Meta Learning NIPS 2022
On the Intrinsic Differential Privacy of Bagging IJCAI 2021
Federated f-Differential Privacy AISTATS 2021
Learning and Evaluating a Differentially Private Pre-trained Language Model NAACL 2021
On the Privacy Properties of GAN-generated Samples AISTATS 2021
Learning and Evaluating a Differentially Private Pre-trained Language Model EMNLP 2021
When differential privacy meets NLP: The devil is in the detail EMNLP 2021
Improving Privacy Guarantee and Efficiency of Latent Dirichlet Allocation Model Training Under Differential Privacy EMNLP 2021
Smoothly Bounding User Contributions in Differential Privacy NIPS 2020