SmallGBM: Gradient Boosting with Bayesian Leaf Regularization for Small-Sample Tabular Data
Emelyanov, I. (2026) · DOI: 10.5281/zenodo.21905013
gradient boosting optimized for small datasets — published on PyPI & Zenodo, outperforms XGBoost/LightGBM at n < 1000
personal AI assistant built from first principles — Multi-Head Attention, Positional Encoding, Transformer Encoder
binary classification model for car subscription platform — ROC-AUC 0.706, 1.86M sessions processed
open-source EdTech startup
