51 citations · 102 across the 11 of their papers we have counts for
6 papers · 1 filter
Searching for consistent associations with a multi-environment knockoff filter
Shuangning Li, Matteo Sesia, Yaniv Romano +2
This paper develops a method based on model-X knockoffs to find conditional associations that are consistent across diverse environments, controlling the false discovery rate. The…
Conformal Prediction using Conditional Histograms
Matteo Sesia, Yaniv Romano
This paper develops a conformal method to compute prediction intervals for non-parametric regression that can automatically adapt to skewed data. Leveraging black-box machine learn…
Classification with Valid and Adaptive Coverage
Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
Conformal inference, cross-validation+, and the jackknife+ are hold-out methods that can be combined with virtually any machine learning algorithm to construct prediction sets with…
With Malice Towards None: Assessing Uncertainty via Equalized Coverage
Yaniv Romano, Rina Foygel Barber, Chiara Sabatti +1
An important factor to guarantee a fair use of data-driven recommendation systems is that we should be able to communicate their uncertainty to decision makers. This can be accompl…
Conformalized Quantile Regression
Yaniv Romano, Evan Patterson, Emmanuel J. Candès
Conformal prediction is a technique for constructing prediction intervals that attain valid coverage in finite samples, without making distributional assumptions. Despite this appe…
Deep Knockoffs
Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
This paper introduces a machine for sampling approximate model-X knockoffs for arbitrary and unspecified data distributions using deep generative models. The main idea is to iterat…