Progress & Compress: A scalable framework for continual learning

Progress & Compress: A scalable framework for continual learning. Schwarz, J., Czarnecki, W., Luketina, J., Grabska-Barwinska, A., Teh, Y. W., Pascanu, R., & Hadsell, R. 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 4535–4544, 2018. PMLR.

Paper bibtex

@inproceedings{DBLP:conf/icml/Schwarz0LGTPH18,
  author    = {Jonathan Schwarz and
               Wojciech Czarnecki and
               Jelena Luketina and
               Agnieszka Grabska{-}Barwinska and
               Yee Whye Teh and
               Razvan Pascanu and
               Raia Hadsell},
  editor    = {Jennifer G. Dy and
               Andreas Krause},
  title     = {Progress {\&} Compress: {A} scalable framework for continual learning},
  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     = {4535--4544},
  publisher = {{PMLR}},
  year      = {2018},
  url       = {http://proceedings.mlr.press/v80/schwarz18a.html},
  timestamp = {Wed, 03 Apr 2019 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/conf/icml/Schwarz0LGTPH18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

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