Privacy

A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning NAACL 2021 A Secure and Efficient Federated Learning Framework for NLP EMNLP 2021 Auditing Black-Box Prediction Models for Data Minimization Compliance NeurIPS 2021 Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models NAACL 2021 Bias and Variance of Post-processing in Differential Privacy AAAI 2021 Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics ALT 2021 Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy? ACL 2021 CAFE: Catastrophic Data Leakage in Vertical Federated Learning NeurIPS 2021 Can Audio-Visual Integration Strengthen Robustness Under Multimodal Attacks? CVPR 2021 CaPC Learning: Confidential and Private Collaborative Learning ICLR 2021 CAPE: Context-Aware Private Embeddings for Private Language Learning EMNLP 2021 Certified Robustness to Word Substitution Attack with Differential Privacy NAACL 2021 Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks IJCAI 2021 Circa: Stochastic ReLUs for Private Deep Learning NeurIPS 2021 CLEAR: Clean-Up Sample-Targeted Backdoor in Neural Networks ICCV 2021 Confident Anchor-Induced Multi-Source Free Domain Adaptation NeurIPS 2021 Configurable Privacy-Preserving Automatic Speech Recognition Interspeech 2021 Constrained differentially private federated learning for low-bandwidth devices UAI 2021 Corruption Robust Active Learning NeurIPS 2021 Covariance-Aware Private Mean Estimation Without Private Covariance Estimation NeurIPS 2021 CRFL: Certifiably Robust Federated Learning against Backdoor Attacks ICML 2021 CrypTen: Secure Multi-Party Computation Meets Machine Learning NeurIPS 2021 CRYPTOGRU: Low Latency Privacy-Preserving Text Analysis With GRU EMNLP 2021 CTAB-GAN: Effective Table Data Synthesizing ACML 2021 Data-Free Model Extraction CVPR 2021