Learning Paradigms

FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer IJCAI 2023 FedExP: Speeding Up Federated Averaging via Extrapolation ICLR 2023 Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense NeurIPS 2023 FedFed: Feature Distillation against Data Heterogeneity in Federated Learning NeurIPS 2023 FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning NeurIPS 2023 FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks NeurIPS 2023 FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability AAAI 2023 FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks IJCAI 2023 FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization ICML 2023 FedID: Federated Interactive Distillation for Large-Scale Pretraining Language Models EMNLP 2023 FedL2P: Federated Learning to Personalize NeurIPS 2023 Fed-LAMB: Layer-wise and Dimension-wise Locally Adaptive Federated Learning UAI 2023 FEDLEGAL: The First Real-World Federated Learning Benchmark for Legal NLP ACL 2023 FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance AAAI 2023 FedNAR: Federated Optimization with Normalized Annealing Regularization NeurIPS 2023 FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity IJCAI 2023 FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning IJCAI 2023 FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation IJCAI 2023 FedPD: Federated Open Set Recognition with Parameter Disentanglement ICCV 2023 FedPerC: Federated Learning for Language Generation with Personal and Context Preference Embeddings EACL 2023 FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning ICCV 2023 FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models ACL 2023 FedSampling: A Better Sampling Strategy for Federated Learning IJCAI 2023 FedSeg: Class-Heterogeneous Federated Learning for Semantic Segmentation CVPR 2023 FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy ICLR 2023