Privacy

PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation AAAI 2023 Practical Differentially Private Hyperparameter Tuning with Subsampling NeurIPS 2023 Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study ICCV 2023 Practical privacy-preserving Gaussian process regression via secret sharing UAI 2023 Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems ICML 2023 Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorization Risks In Language Models EMNLP 2023 Principled Approaches for Private Adaptation from a Public Source AISTATS 2023 PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning. NeurIPS 2023 Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation NeurIPS 2023 Privacy- and Utility-Preserving NLP with Anonymized data: A case study of Pseudonymization ACL 2023 Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? NeurIPS 2023 Privacy Attacks on Schedule-Driven Data AAAI 2023 Privacy Auditing with One (1) Training Run NeurIPS 2023 Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design ICML 2023 Privacy Aware Question-Answering System for Online Mental Health Risk Assessment ACL 2023 Privacy-Aware Rejection Sampling JMLR 2023 Privacy Implications of Retrieval-Based Language Models EMNLP 2023 Privacy-Preserved Evolutionary Graph Modeling via Gromov-Wasserstein Autoregression AAAI 2023 Privacy-Preserving Adversarial Facial Features CVPR 2023 Privacy-Preserving Domain Adaptation of Semantic Parsers ACL 2023 Privacy-Preserving Face Recognition Using Random Frequency Components ICCV 2023 Privacy-Preserving Knowledge Transfer through Partial Parameter Sharing ACL 2023 Privacy Preserving Localization via Coordinate Permutations ICCV 2023 Privacy-Preserving Natural Language Processing EACL 2023 Privacy-preserving patient clustering for personalized federated learnings MLHC 2023