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Federated Learning

497 directly classified papers

Papers per year

Papers

FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning AAAI 2024
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise AAAI 2024
Open-Vocabulary Federated Learning with Multimodal Prototyping NAACL 2024
A Huber Loss Minimization Approach to Byzantine Robust Federated Learning AAAI 2024
High-Fidelity Gradient Inversion in Distributed Learning AAAI 2024
Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization AAAI 2024
Concealing Sensitive Samples against Gradient Leakage in Federated Learning AAAI 2024
Task-Agnostic Privacy-Preserving Representation Learning for Federated Learning against Attribute Inference Attacks AAAI 2024
Knowledge Distillation in Federated Learning: A Practical Guide IJCAI 2024
Dirichlet-based Uncertainty Quantification for Personalized Federated Learning with Improved Posterior Networks IJCAI 2024
TurboSVM-FL: Boosting Federated Learning through SVM Aggregation for Lazy Clients AAAI 2024
FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning AAAI 2024
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences NIPS 2024
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NIPS 2024
Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation AAAI 2024
Towards the Robustness of Differentially Private Federated Learning AAAI 2024
Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation AAAI 2024
Federated Graph Learning under Domain Shift with Generalizable Prototypes AAAI 2024
Formal Logic Enabled Personalized Federated Learning through Property Inference AAAI 2024
Data Disparity and Temporal Unavailability Aware Asynchronous Federated Learning for Predictive Maintenance on Transportation Fleets AAAI 2024
FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants AAAI 2024
z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning AAAI 2024
No Prejudice! Fair Federated Graph Neural Networks for Personalized Recommendation AAAI 2024
Federated Learning over Connected Modes NIPS 2024
Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences NIPS 2024