2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.DB2024★ 2 cited
GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs
Juelin Liu, Sandeep Polisetty, Hui Guan +1
Graph pattern matching is a fundamental problem encountered by many common graph mining tasks and the basic building block of several graph mining systems. This paper explores for…
cs.DC2023★ 1 cited
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
Sandeep Polisetty, Juelin Liu, Kobi Falus +4
Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their superior performance in various graph analytical tasks. Mini…
cs.DC2020
Accelerating Graph Sampling for Graph Machine Learning using GPUs
Abhinav Jangda, Sandeep Polisetty, Arjun Guha +1
Representation learning algorithms automatically learn the features of data. Several representation learning algorithms for graph data, such as DeepWalk, node2vec, and GraphSAGE, s…