
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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Deep Quantile Aggregation
Conditional quantile estimation is a key statistical learning challenge ...
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The Implicit Regularization of Stochastic Gradient Flow for Least Squares
We study the implicit regularization of minibatch stochastic gradient d...
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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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Modelling HighDimensional Categorical Data Using Nonconvex Fusion Penalties
We propose a method for estimation in highdimensional linear models wit...
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Local Spectral Clustering of Density Upper Level Sets
We analyze the Personalized PageRank (PPR) algorithm, a local spectral m...
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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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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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A HigherOrder KolmogorovSmirnov Test
We present an extension of the KolmogorovSmirnov (KS) twosample test, ...
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Surprises in HighDimensional Ridgeless Least Squares Interpolation
Interpolators  estimators that achieve zero training error  have att...
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The limits of distributionfree conditional predictive inference
We consider the problem of distributionfree predictive inference, with ...
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PostSelection 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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A ContinuousTime View of Early Stopping for Least Squares Regression
We study the statistical properties of the iterates generated by gradien...
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The Generalized Lasso Problem and Uniqueness
We study uniqueness in the generalized lasso problem, where the penalty ...
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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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Additive Models with Trend Filtering
We consider additive models built with trend filtering, i.e., additive m...
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DistributionFree Predictive Inference For Regression
We develop a general framework for distributionfree predictive inferenc...
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HighDimensional Longitudinal Classification with the Multinomial Fused Lasso
We study regularized estimation in highdimensional longitudinal classif...
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Nonparametric modal regression
Modal regression estimates the local modes of the distribution of Y give...
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Trend Filtering on Graphs
We introduce a family of adaptive estimators on graphs, based on penaliz...
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The Falling Factorial Basis and Its Statistical Applications
We study a novel splinelike basis, which we name the "falling factorial...
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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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Strong rules for discarding predictors in lassotype problems
We consider rules for discarding predictors in lasso regression and rela...
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Ryan J. Tibshirani
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