StarCoder: A general neural ensemble technique to support traditional scholarship, illustrated with a study of the post-Atlantic slave trade

paper, specified "long paper"
Authorship
  1. 1. Thomas Lippincott

    Johns Hopkins University

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We introduce StarCoder, a graph-aware neural autoencoder modell that can be easily used by traditional scholars to leverage current state-of-the-art machine learning architectures. StarCoder has the specific goals of working on a broad range of data without modification, while allowing computer science researchers to easily extend and specialize its behavior. We describe StarCoder and its early successes in support of an ongoing study of the post-Atlantic slave trade.

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Conference Info

In review

ADHO - 2020
"carrefours / intersections"

Hosted at Carleton University, Université d'Ottawa (University of Ottawa)

Ottawa, Ontario, Canada

July 20, 2020 - July 25, 2020

475 works by 1078 authors indexed

Conference cancelled due to coronavirus. Online conference held at https://hcommons.org/groups/dh2020/. Data for this conference were initially prepared and cleaned by May Ning.

Conference website: https://dh2020.adho.org/

References: https://dh2020.adho.org/abstracts/

Series: ADHO (15)

Organizers: ADHO

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