Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares

Rong Zhu. Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares. In Daniel D. Lee, Masashi Sugiyama, Ulrike V. Luxburg, Isabelle Guyon, Roman Garnett, editors, Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain. pages 406-414, 2016. [doi]

@inproceedings{Zhu16-21,
  title = {Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares},
  author = {Rong Zhu},
  year = {2016},
  url = {http://papers.nips.cc/paper/6579-gradient-based-sampling-an-adaptive-importance-sampling-for-least-squares},
  researchr = {https://researchr.org/publication/Zhu16-21},
  cites = {0},
  citedby = {0},
  pages = {406-414},
  booktitle = {Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain},
  editor = {Daniel D. Lee and Masashi Sugiyama and Ulrike V. Luxburg and Isabelle Guyon and Roman Garnett},
}