Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning.

@inproceedings{lucchese-2019-learning, author = {Claudio Lucchese and Franco Maria Nardini and Rama Kumar Pasumarthi and Sebastian Bruch and Michael Bendersky and Xuanhui Wang and Harrie Oosterhuis and Rolf Jagerman and Maarten de Rijke}, editor = {Benjamin Piwowarski and Max Chevalier and \'{E}ric Gaussier and Yoelle Maarek and Jian-Yun Nie and Falk Scholer}, title = {{Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning}}, booktitle = {{Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, Paris, France, July 21-25, 2019}}, pages = {1419--1420}, publisher = {ACM}, year = {2019}, url = {https://doi.org/10.1145/3331184.3334824}, doi = {https://doi.org/10.1145/3331184.3334824} }