Privacy

DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning NeurIPS 2023 Driving Context into Text-to-Text Privatization ACL 2023 Dropout Is NOT All You Need to Prevent Gradient Leakage AAAI 2023 Dropout-Resilient Secure Multi-Party Collaborative Learning with Linear Communication Complexity AISTATS 2023 DynaFed: Tackling Client Data Heterogeneity With Global Dynamics CVPR 2023 Dynamic Personalized Federated Learning with Adaptive Differential Privacy NeurIPS 2023 Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model AAAI 2023 Effectively Using Public Data in Privacy Preserving Machine Learning ICML 2023 Effective passive membership inference attacks in federated learning against overparameterized models ICLR 2023 Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection AISTATS 2023 Efficient Model Updates for Approximate Unlearning of Graph-Structured Data ICLR 2023 Efficient Privacy-Preserving Stochastic Nonconvex Optimization UAI 2023 Emergent and Predictable Memorization in Large Language Models NeurIPS 2023 Empirical Study of Federated Unlearning: Efficiency and Effectiveness ACML 2023 Encrypted Databases Made Secure Yet Maintainable OSDI 2023 Enhancing Fine-Tuning Based Backdoor Defense with Sharpness-Aware Minimization ICCV 2023 Enhancing Privacy Preservation in Federated Learning via Learning Rate Perturbation ICCV 2023 Enhancing textual counterfactual explanation intelligibility through Counterfactual Feature Importance ACL 2023 ERASER: AdvERsArial Sensitive Element Remover for Image Privacy Preservation AAAI 2023 Erasing Concepts from Diffusion Models ICCV 2023 Ethical Considerations for Responsible Data Curation NeurIPS 2023 ETHICIST: Targeted Training Data Extraction Through Loss Smoothed Soft Prompting and Calibrated Confidence Estimation ACL 2023 Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation NeurIPS 2023 Exploring the Benefits of Visual Prompting in Differential Privacy ICCV 2023 Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping ICLR 2023