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09/05/2023
Maximum Mean Discrepancy Meets Neural Networks: The Radon-Kolmogorov-Smirnov Test
Maximum mean discrepancy (MMD) refers to a general class of nonparametri...
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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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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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12/30/2022
The Voronoigram: Minimax Estimation of Bounded Variation Functions From Scattered Data
We consider the problem of estimating a multivariate function f_0 of bou...
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12/04/2022
Coupled Bootstrap Test Error Estimation for Poisson Variables
Test error estimation is a fundamental problem in statistics and machine...
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11/07/2022
Asymptotics of the Sketched Pseudoinverse
We take a random matrix theory approach to random sketching and show an ...
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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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01/28/2022
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States
The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term bu...
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12/29/2021
Multivariate Trend Filtering for Lattice Data
We study a multivariate version of trend filtering, called Kronecker tre...
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12/13/2021
Real-Time Estimation of COVID-19 Infections via Deconvolution and Sensor Fusion
We propose, implement, and evaluate a method to estimate the daily numbe...
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12/12/2021
Recalibrating probabilistic forecasts of epidemics
Distributional forecasts are important for a wide variety of application...
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11/17/2021
Unbiased Risk Estimation in the Normal Means Problem via Coupled Bootstrap Techniques
We study a new method for estimating the risk of an arbitrary estimator ...
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11/14/2021
Minimax Optimal Regression over Sobolev Spaces via Laplacian Eigenmaps on Neighborhood Graphs
In this paper we study the statistical properties of Principal Component...
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06/03/2021
Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
In this paper we study the statistical properties of Laplacian smoothing...
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02/26/2021
Deep Quantile Aggregation
Conditional quantile estimation is a key statistical learning challenge ...
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03/17/2020
The Implicit Regularization of Stochastic Gradient Flow for Least Squares
We study the implicit regularization of mini-batch stochastic gradient d...
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03/09/2020
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems
This paper serves as a postscript of sorts to Tibshirani (2014); Wang et...
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02/28/2020
Modelling High-Dimensional Categorical Data Using Nonconvex Fusion Penalties
We propose a method for estimation in high-dimensional linear models wit...
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11/21/2019
Local Spectral Clustering of Density Upper Level Sets
We analyze the Personalized PageRank (PPR) algorithm, a local spectral m...
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05/27/2019
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights
The Kalman filter (KF) is one of the most widely used tools for data ass...
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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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03/24/2019
A Higher-Order Kolmogorov-Smirnov Test
We present an extension of the Kolmogorov-Smirnov (KS) two-sample test, ...
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03/19/2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Interpolators -- estimators that achieve zero training error -- have att...
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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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12/10/2018
Post-Selection Inference for Changepoint Detection Algorithms with Application to Copy Number Variation Data
Changepoint detection methods are used in many areas of science and engi...
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10/23/2018
A Continuous-Time View of Early Stopping for Least Squares Regression
We study the statistical properties of the iterates generated by gradien...
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05/20/2018
The Generalized Lasso Problem and Uniqueness
We study uniqueness in the generalized lasso problem, where the penalty ...
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07/27/2017
Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso
In exciting new work, Bertsimas et al. (2016) showed that the classical ...
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02/16/2017
Additive Models with Trend Filtering
We consider additive models built with trend filtering, i.e., additive m...
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04/14/2016
Distribution-Free Predictive Inference For Regression
We develop a general framework for distribution-free predictive inferenc...
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01/29/2015
High-Dimensional Longitudinal Classification with the Multinomial Fused Lasso
We study regularized estimation in high-dimensional longitudinal classif...
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12/04/2014
Nonparametric modal regression
Modal regression estimates the local modes of the distribution of Y give...
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10/28/2014
Trend Filtering on Graphs
We introduce a family of adaptive estimators on graphs, based on penaliz...
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05/03/2014
The Falling Factorial Basis and Its Statistical Applications
We study a novel spline-like basis, which we name the "falling factorial...
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04/10/2013
Adaptive piecewise polynomial estimation via trend filtering
We study trend filtering, a recently proposed tool of Kim et al. [SIAM R...
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11/09/2010