《LEARNING MLPS ON GRAPHS: A UNIFIED VIEW OF EFFECTIVENESS, ROBUSTNESS, AND EFFICIENCY》
《Prototypical Graph Contrastive Learning》
《GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning》
联邦框架图：2022/5/4为止看到的最好看的一张
《Knowledge Enhanced GAN for IoT Traffic Generation》
物联网流量数据集知识图
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《Learn from Others and Be Yourself in Heterogeneous Federated Learning》
《Towards Unsupervised Deep Graph Structure Learning》
《Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach》
《Federated Learning with Heterogeneous Architectures using Graph HyperNetworks》
《Model-Contrastive Federated Learning》
《PROMPTFL: Let Federated Participants Cooperatively Learn Prompts Instead**
of Models — Federated Learning in Age of Foundation Model》
《Federated Graph Semantic and Structural Learning》
《Federated Node Classification over Graphs with Latent Link-type Heterogeneity》
《Exploring One-Shot Semi-Supervised Federated Learning with Pre-trained Diffusion Models》
《A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy》
《Graph Structure Learning with Variational Information Bottleneck》
《Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling》
《C-Watcher A Framework for Early Detection of High-Risk Neighborhoods》
《Vertically Federated Graph Neural Network for Privacy-Preserving Node Classifification》
《Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily》
量子位federatedScope推送《未知来源》
《FedGL: Federated Graph Learning Framework with Global Self-Supervision》
《FedGCN: Convergence and Communication Tradeoffs in Federated Training of Graph Convolutional Networks》
《FedCorr: Multi-Stage Federated Learning for Label Noise Correction》
《Split Two-tower Model for Efficient and Privacy-Preserving Cross-device Federated Recommendation》
《Federated Learning on Non-IID Graphs via Structural Knowledge Sharing》
https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/
《LEARNING MLPS ON GRAPHS: A UNIFIED VIEW OF EFFECTIVENESS,ROBUSTNESS, AND EFFICIENCY》
《FedIN: Federated Intermediate Layers Learning for Model Heterogeneity》
SparseVFL: Communication-Efficient Vertical Federated Learning Based on Sparsification of Embeddings and Gradients
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks
GTV: Generating Tabular Data via Vertical Federated Learning
GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning
《FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction》
《PERSONALIZED FEDERATED LEARNING WITH FEATURE ALIGNMENT AND CLASSIFIER COLLABORATION》
《Federated Learning on Non-IID Graphs via Structural Knowledge Sharing》
《Rethinking Federated Learning with Domain Shift: A Prototype View》
《Communication-efficient federated learning via knowledge distillation》
《Communication-efficient federated learning via knowledge distillation》
《Rethinking Federated Learning with Domain Shift: A Prototype View》
