← Application Areas
Machine Learning › Application Areas ›

Privacy

2794 directly classified papers

Papers per year

Papers

Industry-Scale Orchestrated Federated Learning for Drug Discovery AAAI 2023
Functional Renyi Differential Privacy for Generative Modeling NIPS 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy NIPS 2023
Interpreting Disparate Privacy-Utility Tradeoff in Adversarial Learning via Attribute Correlation WACV 2023
Fast Private Kernel Density Estimation via Locality Sensitive Quantization ICML 2023
Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation ICCV 2023
Global Balanced Experts for Federated Long-Tailed Learning ICCV 2023
Multi-Metrics Adaptively Identifies Backdoors in Federated Learning ICCV 2023
Adaptive Image Anonymization in the Context of Image Classification with Neural Networks ICCV 2023
Towards Fair and Selectively Privacy-Preserving Models Using Negative Multi-Task Learning (Student Abstract) AAAI 2023
Gaussian Differential Privacy on Riemannian Manifolds NIPS 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation NIPS 2023
Static and Sequential Malicious Attacks in the Context of Selective Forgetting NIPS 2023
What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Networks ICCV 2023
Anti-DreamBooth: Protecting Users from Personalized Text-to-image Synthesis ICCV 2023
Privacy-Preserving Face Recognition Using Random Frequency Components ICCV 2023
PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting ICCV 2023
Person Re-Identification without Identification via Event anonymization ICCV 2023
Defending Backdoor Attacks on Vision Transformer via Patch Processing AAAI 2023
Copyright-Certified Distillation Dataset: Distilling One Million Coins into One Bitcoin with Your Private Key AAAI 2023
Sparsity-Preserving Differentially Private Training of Large Embedding Models NIPS 2023
Differentially Private Hypothesis Testing for Linear Regression JMLR 2023
Towards Unbounded Machine Unlearning NIPS 2023
Scalable Membership Inference Attacks via Quantile Regression NIPS 2023
SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning NIPS 2023