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cs.LG2024
HGNAS: Hardware-Aware Graph Neural Architecture Search for Edge Devices
Ao Zhou, Jianlei Yang, Yingjie Qi +5
Graph Neural Networks (GNNs) are becoming increasingly popular for graph-based learning tasks such as point cloud processing due to their state-of-the-art (SOTA) performance. Never…
cs.LG2024
GNNavigator: Towards Adaptive Training of Graph Neural Networks via Automatic Guideline Exploration
Tong Qiao, Jianlei Yang, Yingjie Qi +5
Graph Neural Networks (GNNs) succeed significantly in many applications recently. However, balancing GNNs training runtime cost, memory consumption, and attainable accuracy for var…
cs.LG2024
Graph Neural Networks Automated Design and Deployment on Device-Edge Co-Inference Systems
Ao Zhou, Jianlei Yang, Tong Qiao +4
The key to device-edge co-inference paradigm is to partition models into computation-friendly and computation-intensive parts across the device and the edge, respectively. However,…