%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 }