Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "Graph Neural Networks"
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CHARGE: Accelerating GNN Training via CPU Sampling in Heterogeneous CPU–GPU Environment
Graph Neural Networks (GNNs) have demonstrated exceptional performance across a wide range of applications, driving their widespread adoption. Current frameworks employ CPU and GPU resources—either in isolation or ... -
Neural Models for Personalized Recommendation Systems with External Information
Personalized recommendation systems use the data generated by user-item interactions (for example, in the form of ratings) to predict different users interests in available items and recommend a set of items or products ...