A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise

Xi C. Chen, Yuanshun Yao, Sichao Shi, Snigdhansu Chatterjee, Vipin Kumar, James H. Faghmous. A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise. In Sanjay Chawla Venkatasubramanian, Wagner Meira Jr., editors, Proceedings of the 2016 SIAM International Conference on Data Mining, Miami, Florida, USA, May 5-7, 2016. pages 162-170, SIAM, 2016. [doi]

@inproceedings{ChenYSCKF16,
  title = {A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise},
  author = {Xi C. Chen and Yuanshun Yao and Sichao Shi and Snigdhansu Chatterjee and Vipin Kumar and James H. Faghmous},
  year = {2016},
  doi = {10.1137/1.9781611974348.19},
  url = {http://dx.doi.org/10.1137/1.9781611974348.19},
  researchr = {https://researchr.org/publication/ChenYSCKF16},
  cites = {0},
  citedby = {0},
  pages = {162-170},
  booktitle = {Proceedings of the 2016 SIAM International Conference on Data Mining, Miami, Florida, USA, May 5-7, 2016},
  editor = {Sanjay Chawla Venkatasubramanian and Wagner Meira Jr.},
  publisher = {SIAM},
  isbn = {978-1-61197-434-8},
}