FVR-SGD: A New Flexible Variance-Reduction Method for SGD on Large-Scale Datasets

Mingxing Tang, Zhen Huang, Linbo Qiao, Shuyang Du, Yuxing Peng, Changjian Wang. FVR-SGD: A New Flexible Variance-Reduction Method for SGD on Large-Scale Datasets. In Long Cheng 0001, Andrew Chi-Sing Leung, Seiichi Ozawa, editors, Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part II. Volume 11302 of Lecture Notes in Computer Science, pages 181-193, Springer, 2018. [doi]

@inproceedings{TangHQDPW18,
  title = {FVR-SGD: A New Flexible Variance-Reduction Method for SGD on Large-Scale Datasets},
  author = {Mingxing Tang and Zhen Huang and Linbo Qiao and Shuyang Du and Yuxing Peng and Changjian Wang},
  year = {2018},
  doi = {10.1007/978-3-030-04179-3_16},
  url = {https://doi.org/10.1007/978-3-030-04179-3_16},
  researchr = {https://researchr.org/publication/TangHQDPW18},
  cites = {0},
  citedby = {0},
  pages = {181-193},
  booktitle = {Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part II},
  editor = {Long Cheng 0001 and Andrew Chi-Sing Leung and Seiichi Ozawa},
  volume = {11302},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-04179-3},
}