7 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 7 cited
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity
Mucong Ding, Tahseen Rabbani, Bang An +2
Graph Neural Networks (GNNs) are widely applied to graph learning problems such as node classification. When scaling up the underlying graphs of GNNs to a larger size, we are force…
cs.LG2024
conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks
Tahseen Rabbani, Jiahao Su, Xiaoyu Liu +3
Modern ConvNets continue to achieve state-of-the-art results over a vast array of vision and image classification tasks, but at the cost of increasing parameters. One strategy for…
cs.LG2023
Large-Scale Distributed Learning via Private On-Device Locality-Sensitive Hashing
Tahseen Rabbani, Marco Bornstein, Furong Huang
Locality-sensitive hashing (LSH) based frameworks have been used efficiently to select weight vectors in a dense hidden layer with high cosine similarity to an input, enabling dyna…