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Found 5 papers, 4 papers with code
Addressing Heterogeneity in Federated Learning via Distributional Transformation
Federated learning (FL) allows multiple clients to collaboratively train a deep learning model.
RFID-Based Indoor Spatial Query Evaluation with Bayesian Filtering Techniques
Based on the inference method and tracking models, we develop innovative indoor range and k nearest neighbor (kNN) query algorithms.
CDGNet: A Cross-Time Dynamic Graph-based Deep Learning Model for Traffic Forecasting
Besides, we propose a novel encoder-decoder architecture to incorporate the cross-time dynamic graph-based GCN for multi-step traffic forecasting.
MGC: A Complex-Valued Graph Convolutional Network for Directed Graphs
We test our model on several graph datasets including directed homogeneous and heterogeneous graphs.
Practical Blind Membership Inference Attack via Differential Comparisons
The success of the former heavily depends on the quality of the shadow model, i. e., the transferability between the shadow and the target; the latter, given only blackbox probing access to the target model, cannot make an effective inference of unknowns, compared with MI attacks using shadow models, due to the insufficient number of qualified samples labeled with ground truth membership information.
