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07/31/2023
Conformal PID Control for Time Series Prediction
We study the problem of uncertainty quantification for time series predi...
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07/18/2023
Model-free selective inference under covariate shift via weighted conformal p-values
This paper introduces weighted conformal p-values for model-free selecti...
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05/22/2023
Conformal Prediction With Conditional Guarantees
We consider the problem of constructing distribution-free prediction set...
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05/05/2023
Statistical Inference for Fairness Auditing
Before deploying a black-box model in high-stakes problems, it is import...
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04/08/2023
De Finetti's Theorem and Related Results for Infinite Weighted Exchangeable Sequences
De Finetti's theorem, also called the de Finetti-Hewitt-Savage theorem, ...
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10/04/2022
Selection by Prediction with Conformal p-values
Decision making or scientific discovery pipelines such as job hiring and...
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08/18/2022
An Adaptively Resized Parametric Bootstrap for Inference in High-dimensional Generalized Linear Models
Accurate statistical inference in logistic regression models remains a c...
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04/28/2022
Generalized permutation tests
Permutation tests are an immensely popular statistical tool, used for te...
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02/27/2022
Conformal prediction beyond exchangeability
Conformal prediction is a popular, modern technique for providing valid ...
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11/23/2021
Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach
We propose a model-free framework for sensitivity analysis of individual...
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10/06/2021
Deploying the Conditional Randomization Test in High Multiplicity Problems
This paper introduces the sequential CRT, which is a variable selection ...
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10/03/2021
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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03/17/2021
Conformalized Survival Analysis
Existing survival analysis techniques heavily rely on strong modelling a...
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02/16/2021
Distribution-Free Conditional Median Inference
We consider the problem of constructing confidence intervals for the med...
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07/30/2020
A Power Analysis for Knockoffs with the Lasso Coefficient-Difference Statistic
In a linear model with possibly many predictors, we consider variable se...
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06/11/2020
Conformal Inference of Counterfactuals and Individual Treatment Effects
Evaluating treatment effect heterogeneity widely informs treatment decis...
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06/08/2020
Interpretable Signal Analysis with Knockoffs Enhances Classification of Bacterial Raman Spectra
Interpretability is important for many applications of machine learning ...
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06/08/2020
Achieving Equalized Odds by Resampling Sensitive Attributes
We present a flexible framework for learning predictive models that appr...
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06/03/2020
Classification with Valid and Adaptive Coverage
Conformal inference, cross-validation+, and the jackknife+ are hold-out ...
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01/25/2020
The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance
We study the distribution of the maximum likelihood estimate (MLE) in hi...
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09/12/2019
A comparison of some conformal quantile regression methods
We compare two recently proposed methods that combine ideas from conform...
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08/15/2019
With Malice Towards None: Assessing Uncertainty via Equalized Coverage
An important factor to guarantee a fair use of data-driven recommendatio...
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05/08/2019
Conformalized Quantile Regression
Conformal prediction is a technique for constructing prediction interval...
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05/08/2019
Predictive inference with the jackknife+
This paper introduces the jackknife+, which is a novel method for constr...
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04/12/2019
Conformal Prediction Under Covariate Shift
We extend conformal prediction methodology beyond the case of exchangeab...
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03/13/2019
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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03/12/2019
The limits of distribution-free conditional predictive inference
We consider the problem of distribution-free predictive inference, with ...
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02/07/2019
Dual-Reference Design for Holographic Coherent Diffraction Imaging
A new reference design is introduced for Holographic Coherent Diffractio...
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01/19/2019
Holographic Phase Retrieval and Optimal Reference Design
A general mathematical framework and recovery algorithm is presented for...
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11/16/2018
Deep Knockoffs
This paper introduces a machine for sampling approximate model-X knockof...
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04/25/2018
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
This paper rigorously establishes that the existence of the maximum like...
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03/19/2018
A modern maximum-likelihood theory for high-dimensional logistic regression
Every student in statistics or data science learns early on that when th...
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01/11/2018
Robust inference with knockoffs
We consider the variable selection problem, which seeks to identify impo...
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06/05/2017
The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square
Logistic regression is used thousands of times a day to fit data, predic...
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05/19/2015
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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03/04/2015
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights
We derive a second-order ordinary differential equation (ODE) which is t...
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01/11/2013
Robust subspace clustering
Subspace clustering refers to the task of finding a multi-subspace repre...
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11/05/2012
Discussion: Latent variable graphical model selection via convex optimization
Discussion of "Latent variable graphical model selection via convex opti...
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12/19/2011