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Tabular data underpins numerous high-impact applications of machine learning from fraud detection to genomics and healthcare.
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Xgboost: A scalable tree boosting system
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Cutmix: Regularization strategy to train strong classifiers with localizable features
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Tabert: Pretraining for joint understanding of textual and tabular data
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Vime: Extending the success of self-and semi-supervised learning to tabular domain
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