model aggregation

Federated Learning from Small Datasets ICLR 2023 Federated Learning With Data-Agnostic Distribution Fusion CVPR 2023 FedGS: Federated Graph-Based Sampling with Arbitrary Client Availability AAAI 2023 FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance AAAI 2023 FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning ICCV 2023 Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion IJCAI 2023 Flexible Model Aggregation for Quantile Regression JMLR 2023 Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy AISTATS 2023 GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting CVPR 2023 Incentive-Boosted Federated Crowdsourcing AAAI 2023 Investigating the Effectiveness of Multiple Expert Models Collaboration EMNLP 2023 Knowledge-Aware Federated Active Learning with Non-IID Data ICCV 2023 Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning AAAI 2023 Modeling with Homophily Driven Heterogeneous Data in Gossip Learning IJCAI 2023 On the Importance and Applicability of Pre-Training for Federated Learning ICLR 2023 On the Strategyproofness of the Geometric Median AISTATS 2023 Personalized Federated Learning with Inferred Collaboration Graphs ICML 2023 Personalized Subgraph Federated Learning ICML 2023 Reducing Training Time in Cross-Silo Federated Learning Using Multigraph Topology ICCV 2023 Tackling Data Heterogeneity in Federated Learning with Class Prototypes AAAI 2023 Towards Attack-tolerant Federated Learning via Critical Parameter Analysis ICCV 2023 Towards Instance-adaptive Inference for Federated Learning ICCV 2023 Towards Unbiased Training in Federated Open-world Semi-supervised Learning ICML 2023 A Multi-Agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning AAAI 2022 Architecture Agnostic Federated Learning for Neural Networks ICML 2022