86 citations · 105 across the 10 of their papers we have counts for
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cs.LG2025★ 2 cited
VS-Graph: Scalable and Efficient Graph Classification Using Hyperdimensional Computing
Hamed Poursiami, Shay Snyder, Guojing Cong +2
Graph classification is a fundamental task in domains ranging from molecular property prediction to materials design. While graph neural networks (GNNs) achieve strong performance…
cs.LG2025
HyperGraphX: Graph Transductive Learning with Hyperdimensional Computing and Message Passing
Guojing Cong, Tom Potok, Hamed Poursiami +1
We present a novel algorithm, \hdgc, that marries graph convolution with binding and bundling operations in hyperdimensional computing for transductive graph learning. For predicti…
cs.LG2017★ 86 cited
On the convergence properties of a -step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou, Guojing Cong
Despite their popularity, the practical performance of asynchronous stochastic gradient descent methods (ASGD) for solving large scale machine learning problems are not as good as…