SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives

Aaron Defazio, Francis R. Bach, Simon Lacoste-Julien. SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. In Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger, editors, Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. pages 1646-1654, 2014. [doi]

@inproceedings{DefazioBL14,
  title = {SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives},
  author = {Aaron Defazio and Francis R. Bach and Simon Lacoste-Julien},
  year = {2014},
  url = {http://papers.nips.cc/paper/5258-saga-a-fast-incremental-gradient-method-with-support-for-non-strongly-convex-composite-objectives},
  researchr = {https://researchr.org/publication/DefazioBL14},
  cites = {0},
  citedby = {0},
  pages = {1646-1654},
  booktitle = {Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada},
  editor = {Zoubin Ghahramani and Max Welling and Corinna Cortes and Neil D. Lawrence and Kilian Q. Weinberger},
}