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Found 3 papers, 1 papers with code
A Vertical Federated Learning Framework for Graph Convolutional Network
Recently, Graph Neural Network (GNN) has achieved remarkable success in various real-world problems on graph data.
Software-Defined Edge Computing: A New Architecture Paradigm to Support IoT Data Analysis
We further present an experiment on data anomaly detection in this architecture, and the comparison between two architectures for ECG diagnosis.
Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning
In this paper, we present a graph-aware encoder-decoder framework to learn a generalizable resource allocation strategy that can properly distribute computation tasks of stream processing graphs unobserved from training data.
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