Ryan J. Tibshirani

Orcid: 0000-0002-2158-8304

According to our database1, Ryan J. Tibshirani authored at least 41 papers between 2008 and 2024.

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Bibliography

2024
Asymptotics of the Sketched Pseudoinverse.
SIAM J. Math. Data Sci., March, 2024

Revisiting Optimism and Model Complexity in the Wake of Overparameterized Machine Learning.
CoRR, 2024

Optimal Ridge Regularization for Out-of-Distribution Prediction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Flexible Model Aggregation for Quantile Regression.
J. Mach. Learn. Res., 2023

Maximum Mean Discrepancy Meets Neural Networks: The Radon-Kolmogorov-Smirnov Test.
CoRR, 2023

Class-Conditional Conformal Prediction with Many Classes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Conformal PID Control for Time Series Prediction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Recalibrating probabilistic forecasts of epidemics.
PLoS Comput. Biol., December, 2022

Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems.
Found. Trends Mach. Learn., 2022

The Voronoigram: Minimax Estimation of Bounded Variation Functions From Scattered Data.
CoRR, 2022

Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge Regression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Epidemic tracking and forecasting: Lessons learned from a tumultuous year.
Proc. Natl. Acad. Sci. USA, 2021

Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs.
J. Mach. Learn. Res., 2021

Multivariate Trend Filtering for Lattice Data.
CoRR, 2021

Deep Quantile Aggregation.
CoRR, 2021

Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
The Implicit Regularization of Stochastic Gradient Flow for Least Squares.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation.
CoRR, 2019

Conformal Prediction Under Covariate Shift.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Higher-Order Kolmogorov-Smirnov Test.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

A Continuous-Time View of Early Stopping for Least Squares Regression.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions.
PLoS Comput. Biol., 2018

2017
A human judgment approach to epidemiological forecasting.
PLoS Comput. Biol., 2017

The DFS Fused Lasso: Linear-Time Denoising over General Graphs.
J. Mach. Learn. Res., 2017

Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Trend Filtering on Graphs.
J. Mach. Learn. Res., 2016

Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Multiple Quantile Graphical Model.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Graph Sparsification Approaches for Laplacian Smoothing.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Flexible Modeling of Epidemics with an Empirical Bayes Framework.
PLoS Comput. Biol., 2015

A general framework for fast stagewise algorithms.
J. Mach. Learn. Res., 2015

2014
Fast and Flexible ADMM Algorithms for Trend Filtering.
CoRR, 2014

Efficient Implementations of the Generalized Lasso Dual Path Algorithm.
CoRR, 2014

The Falling Factorial Basis and Its Statistical Applications.
Proceedings of the 31th International Conference on Machine Learning, 2014

2011
Nearly-Isotonic Regression.
Technometrics, 2011

2008
Fast computation of the median by successive binning
CoRR, 2008


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