Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies

Haohan Wang, Bryon Aragam, Eric P. Xing. Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies. In Xiaohua Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Yang Gong, Dmitry Korkin, Illhoi Yoo, Jane Huiru Zheng, editors, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, MO, USA, November 13-16, 2017. pages 431-438, IEEE Computer Society, 2017. [doi]

@inproceedings{WangAX17,
  title = {Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies},
  author = {Haohan Wang and Bryon Aragam and Eric P. Xing},
  year = {2017},
  doi = {10.1109/BIBM.2017.8217687},
  url = {http://doi.ieeecomputersociety.org/10.1109/BIBM.2017.8217687},
  researchr = {https://researchr.org/publication/WangAX17},
  cites = {0},
  citedby = {0},
  pages = {431-438},
  booktitle = {2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, MO, USA, November 13-16, 2017},
  editor = {Xiaohua Hu and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Yang Gong and Dmitry Korkin and Illhoi Yoo and Jane Huiru Zheng},
  publisher = {IEEE Computer Society},
  isbn = {978-1-5090-3050-7},
}