Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Subject "GNN"
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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 ... -
Graph Clustering Approaches for Speaker Diarization of Conversational Speech
In this era of advanced machine intelligence, real-world speech applications need to be equipped to deal with conversations involving multiple speakers. An essential first step in speech information extraction from ...