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Federated Learning

1355 directly classified papers

Papers per year

Papers

FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment IJCAI 2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning ICCV 2023
zPROBE: Zero Peek Robustness Checks for Federated Learning ICCV 2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples ICCV 2023
Generative Gradient Inversion via Over-Parameterized Networks in Federated Learning ICCV 2023
Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation ICCV 2023
L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning ICCV 2023
TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation ICCV 2023
FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning ICCV 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization ICCV 2023
No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier ICCV 2023
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation ICCV 2023
Bold but Cautious: Unlocking the Potential of Personalized Federated Learning through Cautiously Aggressive Collaboration ICCV 2023
Tangent Model Composition for Ensembling and Continual Fine-tuning ICCV 2023
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat ICCV 2023
Robust Heterogeneous Federated Learning under Data Corruption ICCV 2023
Personalized Semantics Excitation for Federated Image Classification ICCV 2023
Moving-Landmark Assisted Distributed Learning Based Decentralized Cooperative Localization (DL-DCL) with Fault Tolerance AAAI 2023
Tackling Data Heterogeneity in Federated Learning with Class Prototypes AAAI 2023
Almost Cost-Free Communication in Federated Best Arm Identification AAAI 2023
FedMDFG: Federated Learning with Multi-Gradient Descent and Fair Guidance AAAI 2023
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning AAAI 2023
Efficient Distribution Similarity Identification in Clustered Federated Learning via Principal Angles between Client Data Subspaces AAAI 2023
FedABC: Targeting Fair Competition in Personalized Federated Learning AAAI 2023
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems AAAI 2023