Federated Learning

Federated Linear Contextual Bandits NeurIPS 2021 Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021 Federated Multi-Task Learning under a Mixture of Distributions NeurIPS 2021 Federated Split Task-Agnostic Vision Transformer for COVID-19 CXR Diagnosis NeurIPS 2021 FedMix: Approximation of Mixup under Mean Augmented Federated Learning ICLR 2021 FedRec++: Lossless Federated Recommendation with Explicit Feedback AAAI 2021 FedSpeech: Federated Text-to-Speech with Continual Learning IJCAI 2021 FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout NeurIPS 2021 FLAME: Differentially Private Federated Learning in the Shuffle Model AAAI 2021 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis ICML 2021 Game of Gradients: Mitigating Irrelevant Clients in Federated Learning AAAI 2021 Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix ICML 2021 H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning IJCAI 2021 Hiding Numerical Vectors in Local Private and Shuffled Messages IJCAI 2021 LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy IJCAI 2021 Learning from History for Byzantine Robust Optimization ICML 2021 Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NeurIPS 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NeurIPS 2021 Linear Regression over Networks with Communication Guarantees L4DC 2021 Local SGD: Unified Theory and New Efficient Methods AISTATS 2021 Lossless Compression of Efficient Private Local Randomizers ICML 2021 MARINA: Faster Non-Convex Distributed Learning with Compression ICML 2021 Model-Contrastive Federated Learning CVPR 2021 Model Linkage Selection for Cooperative Learning JMLR 2021 Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation AAAI 2021