Estimating the principal eigenvector of a stochastic matrix: Mirror Descent Algorithms via game approach with application to PageRank problem

Alexander V. Nazin. Estimating the principal eigenvector of a stochastic matrix: Mirror Descent Algorithms via game approach with application to PageRank problem. In Proceedings of the 49th IEEE Conference on Decision and Control, CDC 2010, December 15-17, 2010, Atlanta, Georgia, USA. pages 792-797, IEEE, 2010. [doi]

@inproceedings{Nazin10,
  title = {Estimating the principal eigenvector of a stochastic matrix: Mirror Descent Algorithms via game approach with application to PageRank problem},
  author = {Alexander V. Nazin},
  year = {2010},
  doi = {10.1109/CDC.2010.5717923},
  url = {http://dx.doi.org/10.1109/CDC.2010.5717923},
  tags = {PageRank, systematic-approach},
  researchr = {https://researchr.org/publication/Nazin10},
  cites = {0},
  citedby = {0},
  pages = {792-797},
  booktitle = {Proceedings of the 49th IEEE Conference on Decision and Control, CDC 2010, December 15-17, 2010, Atlanta, Georgia, USA},
  publisher = {IEEE},
}