federated learning

RSCFed: Random Sampling Consensus Federated Semi-Supervised Learning CVPR 2022 SAGDA: Achieving O(ε^-2) Communication Complexity in Federated Min-Max Learning NeurIPS 2022 SASH: Efficient secure aggregation based on SHPRG for federated learning UAI 2022 Scaling Language Model Size in Cross-Device Federated Learning ACL 2022 SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning NeurIPS 2022 Seizing Critical Learning Periods in Federated Learning AAAI 2022 Self-Aware Personalized Federated Learning NeurIPS 2022 Semi-FedSER: Semi-supervised Learning for Speech Emotion Recognition On Federated Learning using Multiview Pseudo-Labeling Interspeech 2022 SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training NeurIPS 2022 Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NeurIPS 2022 Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection IJCAI 2022 SmartIdx: Reducing Communication Cost in Federated Learning by Exploiting the CNNs Structures AAAI 2022 SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression NeurIPS 2022 SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification AISTATS 2022 SplitFed: When Federated Learning Meets Split Learning AAAI 2022 SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data AAAI 2022 Statistical Estimation and Online Inference via Local SGD COLT 2022 Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology ICML 2022 Taming Fat-Tailed (“Heavier-Tailed” with Potentially Infinite Variance) Noise in Federated Learning NeurIPS 2022 TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels NeurIPS 2022 The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning ICML 2022 The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure Aggregation ICML 2022 Towards Federated Bayesian Network Structure Learning with Continuous Optimization AISTATS 2022 Towards Model Agnostic Federated Learning Using Knowledge Distillation ICLR 2022 Towards Understanding Biased Client Selection in Federated Learning AISTATS 2022