4 citations · 4 across the 1 of their papers we have counts for
4 papers · 1 filter
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models
Ajay Jaiswal, Shiwei Liu, Tianlong Chen +2
Large pre-trained transformers have been receiving explosive attention in the past few years, due to their wide adaptability for numerous downstream applications via fine-tuning, b…
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication
Ajay Jaiswal, Shiwei Liu, Tianlong Chen +2
Graphs are omnipresent and GNNs are a powerful family of neural networks for learning over graphs. Despite their popularity, scaling GNNs either by deepening or widening suffers fr…
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again
Ajay Jaiswal, Peihao Wang, Tianlong Chen +3
Despite the enormous success of Graph Convolutional Networks (GCNs) in modeling graph-structured data, most of the current GCNs are shallow due to the notoriously challenging probl…
Spending Your Winning Lottery Better After Drawing It
Ajay Kumar Jaiswal, Haoyu Ma, Tianlong Chen +2
Lottery Ticket Hypothesis (LTH) suggests that a dense neural network contains a sparse sub-network that can match the performance of the original dense network when trained in isol…