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20042021
most citedSparsity and Incoherence in Compressive Sampling

2.1k citations · 3.1k across the 27 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

stat.ME2019

A comparison of some conformal quantile regression methods

Matteo Sesia, Emmanuel J. Candès

We compare two recently proposed methods that combine ideas from conformal inference and quantile regression to produce locally adaptive and marginally valid prediction intervals u…

stat.ME2019

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…

stat.ME201951 cited

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…

stat.ME2019

Predictive inference with the jackknife+

Rina Foygel Barber, Emmanuel J. Candes, Aaditya Ramdas +1

This paper introduces the jackknife+, which is a novel method for constructing predictive confidence intervals. Whereas the jackknife outputs an interval centered at the predicted…

stat.ME2019

Conformal Prediction Under Covariate Shift

Ryan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candes +1

We extend conformal prediction methodology beyond the case of exchangeable data. In particular, we show that a weighted version of conformal prediction can be used to compute distr…

stat.ME201918 cited

Rejoinder: "Gene Hunting with Hidden Markov Model Knockoffs"

Matteo Sesia, Chiara Sabatti, Emmanuel J. Candès

In this paper we deepen and enlarge the reflection on the possible advantages of a knockoff approach to genome wide association studies (Sesia et al., 2018), starting from the disc…