Author

Ivan Rubachev

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Preprint Oct 2026

On Data Scaling in Tabular ML: More Data, Better Generalization?

Recent work in tabular machine learning has emphasized the importance of diverse and realistic evaluation settings. The niche of large-scale (1M+) data, however, remains under-explored. To study training-data scaling, we assemble eight real-world tabular datasets with up to around ten million training examples, retaini...

Ivan Rubachev, Н. А. Лазарев, Artem Babenko · 0 citations

Jul 2026

TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning

This work introduces TabPack, an efficient MLP ensemble with strong out-of-the-box performance and reduced reliance on traditional tuning, and specifies ranges from which to sample MLP hyperparameter rather than exact hyperparameter values, which naturally demands less precision for good performance.

Yury Gorishniy, Akim Kotelnikov, Ivan Rubachev et al. · arXiv.org · 0 citations