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ORCIDRyan J. Tibshirani
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2020 – today
- 2024
[j13]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. SIAM J. Math. Data Sci. 6(1): 199-225 (2024)- [c20]Pratik Patil, Yuchen Wu, Ryan J. Tibshirani:
Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent. AISTATS 2024: 2260-2268 - [c19]Pratik Patil, Jin-Hong Du, Ryan J. Tibshirani:
Optimal Ridge Regularization for Out-of-Distribution Prediction. ICML 2024 - [i19]Pratik Patil, Yuchen Wu, Ryan J. Tibshirani:
Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent. CoRR abs/2402.16793 (2024) - [i18]Pratik Patil, Jin-Hong Du
, Ryan J. Tibshirani:
Optimal Ridge Regularization for Out-of-Distribution Prediction. CoRR abs/2404.01233 (2024) - 2023
- [j12]Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani:
Flexible Model Aggregation for Quantile Regression. J. Mach. Learn. Res. 24: 162:1-162:45 (2023) - [c18]Anastasios Angelopoulos, Emmanuel J. Candès, Ryan J. Tibshirani:
Conformal PID Control for Time Series Prediction. NeurIPS 2023 - [c17]Tiffany Ding, Anastasios Angelopoulos, Stephen Bates, Michael I. Jordan, Ryan J. Tibshirani:
Class-Conditional Conformal Prediction with Many Classes. NeurIPS 2023 - [i17]Tiffany Ding, Anastasios N. Angelopoulos, Stephen Bates, Michael I. Jordan, Ryan J. Tibshirani:
Class-Conditional Conformal Prediction With Many Classes. CoRR abs/2306.09335 (2023) - [i16]Anastasios N. Angelopoulos, Emmanuel J. Candès, Ryan J. Tibshirani:
Conformal PID Control for Time Series Prediction. CoRR abs/2307.16895 (2023) - [i15]Seunghoon Paik, Michael Celentano, Alden Green, Ryan J. Tibshirani:
Maximum Mean Discrepancy Meets Neural Networks: The Radon-Kolmogorov-Smirnov Test. CoRR abs/2309.02422 (2023) - 2022
- [j11]Ryan J. Tibshirani:
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems. Found. Trends Mach. Learn. 15(6): 694-846 (2022) - [j10]Aaron Rumack, Ryan J. Tibshirani, Roni Rosenfeld:
Recalibrating probabilistic forecasts of epidemics. PLoS Comput. Biol. 18(12): 1010771 (2022) - [c16]Pratik Patil, Alessandro Rinaldo, Ryan J. Tibshirani:
Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge Regression. AISTATS 2022: 6087-6120 - [i14]Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. CoRR abs/2211.03751 (2022) - [i13]Addison J. Hu, Alden Green, Ryan J. Tibshirani:
The Voronoigram: Minimax Estimation of Bounded Variation Functions From Scattered Data. CoRR abs/2212.14514 (2022) - 2021
- [j9]Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani:
Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs. J. Mach. Learn. Res. 22: 247:1-247:71 (2021) - [j8]Roni Rosenfeld, Ryan J. Tibshirani:
Epidemic tracking and forecasting: Lessons learned from a tumultuous year. Proc. Natl. Acad. Sci. USA 118(51): e2111456118 (2021) - [c15]Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani:
Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs. AISTATS 2021: 2602-2610 - [c14]Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan J. Tibshirani:
Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression. AISTATS 2021: 3178-3186 - [i12]Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani:
Deep Quantile Aggregation. CoRR abs/2103.00083 (2021) - [i11]Aaron Rumack, Ryan J. Tibshirani, Roni Rosenfeld:
Recalibrating probabilistic forecasts of epidemics. CoRR abs/2112.06305 (2021) - [i10]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Addison J. Hu, Ryan J. Tibshirani:
Multivariate Trend Filtering for Lattice Data. CoRR abs/2112.14758 (2021) - 2020
- [c13]Alnur Ali, Edgar Dobriban, Ryan J. Tibshirani:
The Implicit Regularization of Stochastic Gradient Flow for Least Squares. ICML 2020: 233-244 - [i9]Ryan J. Tibshirani:
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems. CoRR abs/2003.03886 (2020) - [i8]Alnur Ali, Edgar Dobriban, Ryan J. Tibshirani:
The Implicit Regularization of Stochastic Gradient Flow for Least Squares. CoRR abs/2003.07802 (2020)
2010 – 2019
- 2019
- [c12]Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani:
A Continuous-Time View of Early Stopping for Least Squares Regression. AISTATS 2019: 1370-1378 - [c11]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani:
A Higher-Order Kolmogorov-Smirnov Test. AISTATS 2019: 2621-2630 - [c10]Ryan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas:
Conformal Prediction Under Covariate Shift. NeurIPS 2019: 2526-2536 - [c9]Maria Jahja, David C. Farrow, Roni Rosenfeld, Ryan J. Tibshirani:
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights. NeurIPS 2019: 13166-13175 - [i7]Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani:
Surprises in High-Dimensional Ridgeless Least Squares Interpolation. CoRR abs/1903.08560 (2019) - [i6]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas, Ryan J. Tibshirani:
A Higher-Order Kolmogorov-Smirnov Test. CoRR abs/1903.10083 (2019) - 2018
- [j7]Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld:
Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions. PLoS Comput. Biol. 14(6) (2018) - [i5]Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani:
A Continuous-Time View of Early Stopping for Least Squares Regression. CoRR abs/1810.10082 (2018) - 2017
- [j6]Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani:
The DFS Fused Lasso: Linear-Time Denoising over General Graphs. J. Mach. Learn. Res. 18: 176:1-176:36 (2017) - [j5]David C. Farrow, Logan C. Brooks, Sangwon Hyun, Ryan J. Tibshirani, Donald S. Burke, Roni Rosenfeld:
A human judgment approach to epidemiological forecasting. PLoS Comput. Biol. 13(3) (2017) - [c8]Ryan J. Tibshirani:
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions. NIPS 2017: 517-528 - [c7]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, James Sharpnack, Ryan J. Tibshirani:
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods. NIPS 2017: 5800-5810 - [c6]Kevin Lin, James Sharpnack, Alessandro Rinaldo, Ryan J. Tibshirani:
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening. NIPS 2017: 6884-6893 - 2016
- [j4]Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. J. Mach. Learn. Res. 17: 105:1-105:41 (2016) - [c5]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan J. Tibshirani:
Graph Sparsification Approaches for Laplacian Smoothing. AISTATS 2016: 1250-1259 - [c4]Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan J. Tibshirani:
Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers. NIPS 2016: 3513-3521 - [c3]Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani:
The Multiple Quantile Graphical Model. NIPS 2016: 3747-3755 - 2015
- [j3]Ryan J. Tibshirani:
A general framework for fast stagewise algorithms. J. Mach. Learn. Res. 16: 2543-2588 (2015) - [j2]Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld:
Flexible Modeling of Epidemics with an Empirical Bayes Framework. PLoS Comput. Biol. 11(8) (2015) - [c2]Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. AISTATS 2015 - 2014
- [c1]Yu-Xiang Wang, Alexander J. Smola, Ryan J. Tibshirani:
The Falling Factorial Basis and Its Statistical Applications. ICML 2014: 730-738 - [i4]Taylor B. Arnold, Ryan J. Tibshirani:
Efficient Implementations of the Generalized Lasso Dual Path Algorithm. CoRR abs/1405.3222 (2014) - [i3]Aaditya Ramdas, Ryan J. Tibshirani:
Fast and Flexible ADMM Algorithms for Trend Filtering. CoRR abs/1406.2082 (2014) - [i2]Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani:
Trend Filtering on Graphs. CoRR abs/1410.7690 (2014) - 2011
- [j1]Ryan J. Tibshirani, Holger Höfling, Robert Tibshirani:
Nearly-Isotonic Regression. Technometrics 53(1): 54-61 (2011)
2000 – 2009
- 2008
- [i1]Ryan J. Tibshirani:
Fast computation of the median by successive binning. CoRR abs/0806.3301 (2008)
Coauthor Index
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