Richard Leibrandt, Stephan Günnemann. Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation. In Martin Ester, Dino Pedreschi, editors, Proceedings of the 2018 SIAM International Conference on Data Mining, SDM 2018, May 3-5, 2018, San Diego Marriott Mission Valley, San Diego, CA, USA. pages 747-755, SIAM, 2018. [doi]
@inproceedings{LeibrandtG18,
title = {Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation},
author = {Richard Leibrandt and Stephan Günnemann},
year = {2018},
doi = {10.1137/1.9781611975321.84},
url = {https://doi.org/10.1137/1.9781611975321.84},
researchr = {https://researchr.org/publication/LeibrandtG18},
cites = {0},
citedby = {0},
pages = {747-755},
booktitle = {Proceedings of the 2018 SIAM International Conference on Data Mining, SDM 2018, May 3-5, 2018, San Diego Marriott Mission Valley, San Diego, CA, USA},
editor = {Martin Ester and Dino Pedreschi},
publisher = {SIAM},
isbn = {978-1-61197-532-1},
}