Backward-Compatible Prediction Updates: A Probabilistic Approach

Frederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler. Backward-Compatible Prediction Updates: A Probabilistic Approach. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 116-128, 2021. [doi]

@inproceedings{TraubleKKLSG21,
  title = {Backward-Compatible Prediction Updates: A Probabilistic Approach},
  author = {Frederik Träuble and Julius von Kügelgen and Matthäus Kleindessner and Francesco Locatello and Bernhard Schölkopf and Peter V. Gehler},
  year = {2021},
  url = {https://proceedings.neurips.cc/paper/2021/hash/012d9fe15b2493f21902cd55603382ec-Abstract.html},
  researchr = {https://researchr.org/publication/TraubleKKLSG21},
  cites = {0},
  citedby = {0},
  pages = {116-128},
  booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
  editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}