← Search

Andrey Gulin

2 accepted papers

2023

Which Tricks are Important for Learning to Rank?

ICML 2023poster

Nowadays, state-of-the-art learning-to-rank methods are based on gradient-boosted decision trees (GBDT). The most well-known algorithm is LambdaMART which was proposed more than a decade ago. Recently, several other GBDT-based ranking algorithms were proposed. In this paper, we thoroughly analyze th…

Cited by 12SourcePDFScholar
2018

CatBoost: unbiased boosting with categorical features

NeurIPS 2018poster

This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit. Their combination leads to CatBoost outperforming other publicly available boosting implementations in terms of quality on a variety of datasets. Two critical algorithmic advances introduced in CatBo…