111 citations · 287 across the 8 of their papers we have counts for
8 papers
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching
Tim Kaler, Alexandros-Stavros Iliopoulos, Philip Murzynowski +3
Training and inference with graph neural networks (GNNs) on massive graphs has been actively studied since the inception of GNNs, owing to the widespread use and success of GNNs in…
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler, Nickolas Stathas, Anne Ouyang +4
Improving the training and inference performance of graph neural networks (GNNs) is faced with a challenge uncommon in general neural networks: creating mini-batches requires a lot…
Multidimensional Included and Excluded Sums
Helen Xu, Sean Fraser, Charles E. Leiserson
This paper presents algorithms for the included-sums and excluded-sums problems used by scientific computing applications such as the fast multipole method. These problems are defi…
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Mark Weber, Giacomo Domeniconi, Jie Chen +4
Anti-money laundering (AML) regulations play a critical role in safeguarding financial systems, but bear high costs for institutions and drive financial exclusion for those on the…
Scalable Graph Learning for Anti-Money Laundering: A First Look
Mark Weber, Jie Chen, Toyotaro Suzumura +6
Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150,000 people since 2006, upwards of 700,000 people per year are "exported" i…
On the Efficiency of Localized Work Stealing
Warut Suksompong, Charles E. Leiserson, Tao B. Schardl
This paper investigates a variant of the work-stealing algorithm that we call the localized work-stealing algorithm. The intuition behind this variant is that because of locality,…
Upper Bounds on Number of Steals in Rooted Trees
Charles E. Leiserson, Tao B. Schardl, Warut Suksompong
Inspired by applications in parallel computing, we analyze the setting of work stealing in multithreaded computations. We obtain tight upper bounds on the number of steals when the…
Standards for Graph Algorithm Primitives
Tim Mattson, David Bader, Jon Berry +16
It is our view that the state of the art in constructing a large collection of graph algorithms in terms of linear algebraic operations is mature enough to support the emergence of…