Sampling Without Compromising Accuracy in Adaptive Data Analysis

Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein. Sampling Without Compromising Accuracy in Adaptive Data Analysis. In Aryeh Kontorovich, Gergely Neu, editors, Algorithmic Learning Theory, ALT 2020, 8-11 February 2020, San Diego, CA, USA. Volume 117 of Proceedings of Machine Learning Research, pages 297-318, PMLR, 2020. [doi]

@inproceedings{FishRR20,
  title = {Sampling Without Compromising Accuracy in Adaptive Data Analysis},
  author = {Benjamin Fish and Lev Reyzin and Benjamin I. P. Rubinstein},
  year = {2020},
  url = {http://proceedings.mlr.press/v117/fish20a.html},
  researchr = {https://researchr.org/publication/FishRR20},
  cites = {0},
  citedby = {0},
  pages = {297-318},
  booktitle = {Algorithmic Learning Theory, ALT 2020, 8-11 February 2020, San Diego, CA, USA},
  editor = {Aryeh Kontorovich and Gergely Neu},
  volume = {117},
  series = {Proceedings of Machine Learning Research},
  publisher = {PMLR},
}