Privacy

Private Isotonic Regression NeurIPS 2022 PrivateMail: Supervised Manifold Learning of Deep Features with Privacy for Image Retrieval AAAI 2022 Private Matrix Approximation and Geometry of Unitary Orbits COLT 2022 Private Multiparty Perception for Navigation NeurIPS 2022 Private optimization in the interpolation regime: faster rates and hardness results ICML 2022 Private Rank Aggregation in Central and Local Models AAAI 2022 Private Robust Estimation by Stabilizing Convex Relaxations COLT 2022 Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size AISTATS 2022 Private Set Generation with Discriminative Information NeurIPS 2022 PrivateSNN: Privacy-Preserving Spiking Neural Networks AAAI 2022 Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited IJCAI 2022 Private Streaming SCO in ℓ_p geometry with Applications in High Dimensional Online Decision Making ICML 2022 Private Synthetic Data for Multitask Learning and Marginal Queries NeurIPS 2022 Privid: Practical, Privacy-Preserving Video Analytics Queries NSDI 2022 Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization NeurIPS 2022 Protecting Intellectual Property of Language Generation APIs with Lexical Watermark AAAI 2022 Provably Confidential Language Modelling NAACL 2022 PROVES: Establishing Image Provenance Using Semantic Signatures WACV 2022 PUMA: Performance Unchanged Model Augmentation for Training Data Removal AAAI 2022 Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks EMNLP 2022 Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets NeurIPS 2022 Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NeurIPS 2022 Reconstructing Test Labels from Noisy Loss Functions AISTATS 2022 Reconstructing Training Data From Diverse ML Models by Ensemble Inversion WACV 2022 Reconstructing Training Data From Trained Neural Networks NeurIPS 2022