%0 Conference Paper
%1 grinsztajn2022tree
%A Grinsztajn, Leo
%A Oyallon, Edouard
%A Varoquaux, Gael
%B Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track
%D 2022
%K citedby:scholar:count:5 citedby:scholar:timestamp:2022-12-1 comparison data decision evaluation forest learning machine ml network neural nn performance random tabular tree trees
%T Why do tree-based models still outperform deep learning on typical tabular data?
@inproceedings{grinsztajn2022tree,
added-at = {2022-12-01T16:30:02.000+0100},
author = {Grinsztajn, Leo and Oyallon, Edouard and Varoquaux, Gael},
biburl = {https://www.bibsonomy.org/bibtex/2297106cf785749acfa15d55ea2b33b83/becker},
booktitle = {Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
interhash = {270fbc12390a268d7ad4b845d452e38d},
intrahash = {297106cf785749acfa15d55ea2b33b83},
keywords = {citedby:scholar:count:5 citedby:scholar:timestamp:2022-12-1 comparison data decision evaluation forest learning machine ml network neural nn performance random tabular tree trees},
timestamp = {2022-12-02T12:35:47.000+0100},
title = {Why do tree-based models still outperform deep learning on typical tabular data?},
year = 2022
}