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Found 3 papers, 2 papers with code
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
Therefore, mini-batch training for graph transformers is a promising direction, but limited samples in each mini-batch can not support effective dense attention to encode informative representations.
MG-GCN: Scalable Multi-GPU GCN Training Framework
Full batch training of Graph Convolutional Network (GCN) models is not feasible on a single GPU for large graphs containing tens of millions of vertices or more.
On Symmetric Rectilinear Matrix Partitioning
More specifically, in this work, we address the problem of symmetric rectilinear partitioning of a square matrix.
Data Structures and Algorithms
