Universal Approximation Functions for Fast Learning to Rank: Replacing Expensive Regression Forests with Simple Feed-Forward Networks.

@inproceedings{cohen-2018-universal, author = {Daniel Cohen and John Foley and Hamed Zamani and James Allan and W. Bruce Croft}, editor = {Kevyn Collins-Thompson and Qiaozhu Mei and Brian D. Davison and Yiqun Liu and Emine Yilmaz}, title = {{Universal Approximation Functions for Fast Learning to Rank: Replacing Expensive Regression Forests with Simple Feed-Forward Networks}}, booktitle = {{The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, SIGIR 2018, Ann Arbor, MI, USA, July 08-12, 2018}}, pages = {1017--1020}, publisher = {ACM}, year = {2018}, url = {https://doi.org/10.1145/3209978.3210137}, doi = {https://doi.org/10.1145/3209978.3210137} }