Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning. Neel, S., Roth, A., & Sharifi-Malvajerdi, S. In Feldman, V., Ligett, K., & Sabato, S., editors, Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide, volume 132, of Proceedings of Machine Learning Research, pages 931–962, 2021. PMLR.

Paper bibtex

@inproceedings{DBLP:conf/alt/Neel0S21,
  author       = {Seth Neel and
                  Aaron Roth and
                  Saeed Sharifi{-}Malvajerdi},
  editor       = {Vitaly Feldman and
                  Katrina Ligett and
                  Sivan Sabato},
  title        = {Descent-to-Delete: Gradient-Based Methods for Machine Unlearning},
  booktitle    = {Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference,
                  Worldwide},
  series       = {Proceedings of Machine Learning Research},
  volume       = {132},
  pages        = {931--962},
  publisher    = {{PMLR}},
  year         = {2021},
  url          = {http://proceedings.mlr.press/v132/neel21a.html},
  timestamp    = {Fri, 26 Mar 2021 15:45:50 +0100},
  biburl       = {https://dblp.org/rec/conf/alt/Neel0S21.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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