Learning Paradigms

Federated Prompt Learning for Weather Foundation Models on Devices IJCAI 2024 Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data NeurIPS 2024 Federated X-armed Bandit AAAI 2024 FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise IJCAI 2024 FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning AAAI 2024 FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting AAAI 2024 FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024 FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning NeurIPS 2024 FedHCA2: Towards Hetero-Client Federated Multi-Task Learning CVPR 2024 FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models EMNLP 2024 FedLF: Layer-Wise Fair Federated Learning AAAI 2024 FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing AAAI 2024 FedMef: Towards Memory-efficient Federated Dynamic Pruning CVPR 2024 FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection NeurIPS 2024 FedMut: Generalized Federated Learning via Stochastic Mutation AAAI 2024 FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning AAAI 2024 FedPFT: Federated Proxy Fine-Tuning of Foundation Models IJCAI 2024 Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity AAAI 2024 FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning CVPR 2024 FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning IJCAI 2024 FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference NeurIPS 2024 FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning IJCAI 2024 FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning AAAI 2024 FedUV: Uniformity and Variance for Heterogeneous Federated Learning CVPR 2024