Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers

Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y., Olshevsky, A., Szepesvári, C., & Saligrama, V. In Dy, J. G. & Krause, A., editors, Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, volume 80, of Proceedings of Machine Learning Research, pages 3341–3350, 2018. PMLR.

Paper bibtex 3 downloads

@inproceedings{DBLP:conf/icml/MaOSS18,
  author       = {Yao Ma and
                  Alexander Olshevsky and
                  Csaba Szepesv{\'{a}}ri and
                  Venkatesh Saligrama},
  editor       = {Jennifer G. Dy and
                  Andreas Krause},
  title        = {Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced
                  Aggregation of Sparsely Interacting Workers},
  booktitle    = {Proceedings of the 35th International Conference on Machine Learning,
                  {ICML} 2018, Stockholmsm{\"{a}}ssan, Stockholm, Sweden, July 10-15,
                  2018},
  series       = {Proceedings of Machine Learning Research},
  volume       = {80},
  pages        = {3341--3350},
  publisher    = {{PMLR}},
  year         = {2018},
  url          = {http://proceedings.mlr.press/v80/ma18b.html},
  timestamp    = {Wed, 03 Apr 2019 18:17:30 +0200},
  biburl       = {https://dblp.org/rec/conf/icml/MaOSS18.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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