Security & Privacy

Parametric Bootstrap for Differentially Private Confidence Intervals AISTATS 2022 Privacy Amplification by Decentralization AISTATS 2022 Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation NeurIPS 2022 Privacy Pitfalls of Online Service Terms and Conditions: a Hybrid Approach for Classification and Summarization EMNLP 2022 Privacy-Preserving Face Recognition in the Frequency Domain AAAI 2022 Privacy-Preserving Models for Legal Natural Language Processing EMNLP 2022 Privacy Preserving Partial Localization CVPR 2022 Privacy-Preserving Text Classification on BERT Embeddings with Homomorphic Encryption NAACL 2022 Private Adaptive Optimization with Side information ICML 2022 Private and Communication-Efficient Algorithms for Entropy Estimation NeurIPS 2022 Private and polynomial time algorithms for learning Gaussians and beyond COLT 2022 Private High-Dimensional Hypothesis Testing COLT 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 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 Streaming SCO in ℓ_p geometry with Applications in High Dimensional Online Decision Making ICML 2022 Provably Confidential Language Modelling NAACL 2022 Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks EMNLP 2022 Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion NeurIPS 2022 Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning NeurIPS 2022 Residue-Based Natural Language Adversarial Attack Detection NAACL 2022