Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems

Dan Garber, Atara Kaplan. Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems. In Kamalika Chaudhuri, Masashi Sugiyama, editors, The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan. Volume 89 of Proceedings of Machine Learning Research, pages 286-294, PMLR, 2019. [doi]

@inproceedings{GarberK19,
  title = {Fast Stochastic Algorithms for Low-rank and Nonsmooth Matrix Problems},
  author = {Dan Garber and Atara Kaplan},
  year = {2019},
  url = {http://proceedings.mlr.press/v89/garber19a.html},
  researchr = {https://researchr.org/publication/GarberK19},
  cites = {0},
  citedby = {0},
  pages = {286-294},
  booktitle = {The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan},
  editor = {Kamalika Chaudhuri and Masashi Sugiyama},
  volume = {89},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}