Federated Learning

Privacy-Preserving Feature Selection with Secure Multiparty Computation ICML 2021 Provably Secure Federated Learning against Malicious Clients AAAI 2021 QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning NeurIPS 2021 Regularized Mutual Learning for Personalized Federated Learning ACML 2021 Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning NeurIPS 2021 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning AISTATS 2021 R-GAP: Recursive Gradient Attack on Privacy ICLR 2021 Robust and differentially private mean estimation NeurIPS 2021 Sageflow: Robust Federated Learning against Both Stragglers and Adversaries NeurIPS 2021 SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract) AAAI 2021 Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating AAAI 2021 Semi-supervised Sequence Classification through Change Point Detection AAAI 2021 Shuffled Model of Differential Privacy in Federated Learning AISTATS 2021 Soteria: Provable Defense Against Privacy Leakage in Federated Learning From Representation Perspective CVPR 2021 STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning NeurIPS 2021 Subgraph Federated Learning with Missing Neighbor Generation NeurIPS 2021 The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation ICML 2021 The Impact of Record Linkage on Learning from Feature Partitioned Data ICML 2021 Towards Flexible Device Participation in Federated Learning AISTATS 2021 Toward Understanding the Influence of Individual Clients in Federated Learning AAAI 2021 Understanding Clinical Collaborations Through Federated Classifier Selection MLHC 2021 Understanding Unintended Memorization in Language Models Under Federated Learning NAACL 2021 Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information AISTATS 2021 Zero-Shot Federated Learning with New Classes for Audio Classification Interspeech 2021 99% of Worker-Master Communication in Distributed Optimization Is Not Needed UAI 2020