**Problem of the Week**

**Math Club**

**BUGCAT 2020**

**Zassenhaus Conference**

**Hilton Memorial Lecture**

seminars:stat:201022

Statistics Seminar

Department of Mathematical Sciences

DATE: | Thursday, Oct. 22, 2020 |
---|---|

TIME: | 1:15pm – 2:15pm |

LOCATION: | zoom meeting |

SPEAKER: | Baozhen Wang, Binghamton University |

TITLE: | Conformal Prediction Under Covariate Shift |

**Abstract**

The authors extend conformal prediction methodology beyond the case of exchangeable data. In particular, they show that a weighted version of conformal prediction can be used to compute distribution-free prediction intervals for problems in which the test and training covariate distributions differ, but the likelihood ratio between these two distributions is known—or, in practice, can be estimated accurately with access to a large set of unlabeled data (test covariate points). Their weighted extension of conformal prediction also applies more generally, to settings in which the data satisﬁes a certain weighted notion of exchangeability.

seminars/stat/201022.txt · Last modified: 2020/10/12 20:25 by qyu

Except where otherwise noted, content on this wiki is licensed under the following license: CC Attribution-Noncommercial-Share Alike 3.0 Unported