Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)

no code implementations • 27 Mar 2020 • Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily Fox, Hugo Larochelle

Reproducibility, that is obtaining similar results as presented in a paper or talk, using the same code and data (when available), is a necessary step to verify the reliability of research findings.

BIG-bench Machine Learning

Textual analysis of artificial intelligence manuscripts reveals features associated with peer review outcome

1 code implementation • 21 Oct 2019 • Philippe Vincent-Lamarre, Vincent Larivière

We found that accepted manuscripts scored lower than rejected manuscripts on two indicators of readability, and that they also used more scientific and artificial intelligence jargon.

Semantic Similarity Semantic Textual Similarity

The Latent Structure of Dictionaries

no code implementations • 1 Nov 2014 • Philippe Vincent-Lamarre, Alexandre Blondin Massé, Marcos Lopes, Mélanie Lord, Odile Marcotte, Stevan Harnad

But the Core cannot define all the rest of the dictionary.