model aggregation

Byzantine-robust Decentralized Federated Learning via Dual-domain Clustering and Trust Bootstrapping CVPR 2024 Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets AAAI 2024 Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction AAAI 2024 Enhancing Byzantine-Resistant Aggregations with Client Embedding EMNLP 2024 Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity CVPR 2024 FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning IJCAI 2024 FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise AAAI 2024 FedAS: Bridging Inconsistency in Personalized Federated Learning CVPR 2024 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update AAAI 2024 FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation ICLR 2024 FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler ICLR 2024 Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning NeurIPS 2024 FedHCA2: Towards Hetero-Client Federated Multi-Task Learning CVPR 2024 FedMut: Generalized Federated Learning via Stochastic Mutation AAAI 2024 Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity AAAI 2024 FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning IJCAI 2024 Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients NeurIPS 2024 Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization ICLR 2024 FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning CVPR 2024 HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links NeurIPS 2024 Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning ICLR 2024 Invariant Aggregator for Defending against Federated Backdoor Attacks AISTATS 2024 Low Precision Local Training is Enough for Federated Learning NeurIPS 2024 LR-XFL: Logical Reasoning-Based Explainable Federated Learning AAAI 2024 NYCU-NLP at SemEval-2024 Task 2: Aggregating Large Language Models in Biomedical Natural Language Inference for Clinical Trials SemEval 2024