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Charles E. Leiserson

Massachusetts Institute of Technology

279

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Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining.

2022 | MLSys
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Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining.

2021 arXiv: Learning
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Multidimensional Included and Excluded Sums.

2021
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Floors and Ceilings in Divide-and-Conquer Recurrences

2021
- William Kuszmaul
- Charles E. Leiserson
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PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation

2021
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Multidimensional Included and Excluded Sums.

2021 arXiv: Data Structures and Algorithms
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There’s plenty of room at the Top

2020 Science
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There’s plenty of room at the Top: What will drive computer performance after Moore’s law?

2020 Science
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Work-Efficient Parallel Algorithms for Accurate Floating-Point Prefix Sums

2020 HPEC | IEEE High Performance Extreme Computing Conference
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Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

2019 arXiv: Social and Information Networks
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