CatBoost: Unbiased Boosting with Categorical Features, Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin, 2018Advances in Neural Information Processing Systems 31 (Curran Associates, Inc.)DOI: 10.48550/arXiv.1706.09516 - This foundational paper introduces CatBoost, including the Ordered Boosting mechanism to mitigate prediction shift and Ordered Target Statistics for categorical feature encoding.
Greedy Function Approximation: A Gradient Boosting Machine, Jerome H. Friedman, 2001The Annals of Statistics, Vol. 29 (Institute of Mathematical Statistics)DOI: 10.1214/aos/1013203451 - This seminal paper introduced the Gradient Boosting Machine (GBM) algorithm, providing the theoretical basis upon which algorithms like CatBoost are built.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Trevor Hastie, Robert Tibshirani, and Jerome Friedman, 2009 (Springer) - A comprehensive textbook that provides a theoretical background on ensemble methods, including gradient boosting (Chapter 10), and discusses model validation relevant to prediction shift.