1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Cached Operator Reordering: A Unified View for Fast GNN Training
Julia Bazinska, Andrei Ivanov, Tal Ben-Nun +4
Graph Neural Networks (GNNs) are a powerful tool for handling structured graph data and addressing tasks such as node classification, graph classification, and clustering. However,…
cs.DC2022★ 1 cited
ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations
Maciej Besta, Cesare Miglioli, Paolo Sylos Labini +11
Important graph mining problems such as Clustering are computationally demanding. To significantly accelerate these problems, we propose ProbGraph: a graph representation that enab…