
Deploying the Conditional Randomization Test in High Multiplicity Problems
This paper introduces the sequential CRT, which is a variable selection ...
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Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
We introduce Learn then Test, a framework for calibrating machine learni...
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Conformalized Survival Analysis
Existing survival analysis techniques heavily rely on strong modelling a...
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DistributionFree Conditional Median Inference
We consider the problem of constructing confidence intervals for the med...
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A Power Analysis for Knockoffs with the Lasso CoefficientDifference Statistic
In a linear model with possibly many predictors, we consider variable se...
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Conformal Inference of Counterfactuals and Individual Treatment Effects
Evaluating treatment effect heterogeneity widely informs treatment decis...
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Interpretable Signal Analysis with Knockoffs Enhances Classification of Bacterial Raman Spectra
Interpretability is important for many applications of machine learning ...
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Achieving Equalized Odds by Resampling Sensitive Attributes
We present a flexible framework for learning predictive models that appr...
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Classification with Valid and Adaptive Coverage
Conformal inference, crossvalidation+, and the jackknife+ are holdout ...
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The Asymptotic Distribution of the MLE in Highdimensional Logistic Models: Arbitrary Covariance
We study the distribution of the maximum likelihood estimate (MLE) in hi...
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A comparison of some conformal quantile regression methods
We compare two recently proposed methods that combine ideas from conform...
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With Malice Towards None: Assessing Uncertainty via Equalized Coverage
An important factor to guarantee a fair use of datadriven recommendatio...
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Conformalized Quantile Regression
Conformal prediction is a technique for constructing prediction interval...
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Predictive inference with the jackknife+
This paper introduces the jackknife+, which is a novel method for constr...
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Conformal Prediction Under Covariate Shift
We extend conformal prediction methodology beyond the case of exchangeab...
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Rejoinder: "Gene Hunting with Hidden Markov Model Knockoffs"
In this paper we deepen and enlarge the reflection on the possible advan...
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The limits of distributionfree conditional predictive inference
We consider the problem of distributionfree predictive inference, with ...
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DualReference Design for Holographic Coherent Diffraction Imaging
A new reference design is introduced for Holographic Coherent Diffractio...
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Holographic Phase Retrieval and Optimal Reference Design
A general mathematical framework and recovery algorithm is presented for...
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Deep Knockoffs
This paper introduces a machine for sampling approximate modelX knockof...
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The phase transition for the existence of the maximum likelihood estimate in highdimensional logistic regression
This paper rigorously establishes that the existence of the maximum like...
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A modern maximumlikelihood theory for highdimensional logistic regression
Every student in statistics or data science learns early on that when th...
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Robust inference with knockoffs
We consider the variable selection problem, which seeks to identify impo...
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The Likelihood Ratio Test in HighDimensional Logistic Regression Is Asymptotically a Rescaled ChiSquare
Logistic regression is used thousands of times a day to fit data, predic...
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Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
We consider the fundamental problem of solving quadratic systems of equa...
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A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
We derive a secondorder ordinary differential equation (ODE) which is t...
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Robust subspace clustering
Subspace clustering refers to the task of finding a multisubspace repre...
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Discussion: Latent variable graphical model selection via convex optimization
Discussion of "Latent variable graphical model selection via convex opti...
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A geometric analysis of subspace clustering with outliers
This paper considers the problem of clustering a collection of unlabeled...
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Emmanuel J. Candès
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