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cs.LG2024
DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling
Ningyi Liao, Zihao Yu, Siqiang Luo
Graph Transformer (GT) has recently emerged as a promising neural network architecture for learning graph-structured data. However, its global attention mechanism with quadratic co…
cs.DB2024★ 1 cited
CAMAL: Optimizing LSM-trees via Active Learning
Weiping Yu, Siqiang Luo, Zihao Yu +1
We use machine learning to optimize LSM-tree structure, aiming to reduce the cost of processing various read/write operations. We introduce a new approach Camal, which boasts the f…
cs.LG2024
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Ningyi Liao, Zihao Yu, Ruixiao Zeng +1
Graph Neural Networks (GNNs) have shown promising performance, but at the cost of resource-intensive operations on graph-scale matrices. To reduce computational overhead, previous…