Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality

Changxiao Cai, H. Vincent Poor, Yuxin Chen 0002. Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event. Volume 119 of Proceedings of Machine Learning Research, pages 1271-1282, PMLR, 2020. [doi]

@inproceedings{CaiP020,
  title = {Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality},
  author = {Changxiao Cai and H. Vincent Poor and Yuxin Chen 0002},
  year = {2020},
  url = {http://proceedings.mlr.press/v119/cai20c.html},
  researchr = {https://researchr.org/publication/CaiP020},
  cites = {0},
  citedby = {0},
  pages = {1271-1282},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event},
  volume = {119},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}