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Conformal inference, cross-validation+, and the jackknife+ are hold-out methods that can be combined with virtually any machine learning algorithm to construct prediction sets with guaranteed marginal coverage.
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
J. Platt · 1999
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A quantile regression neural network approach to estimating the conditional density of multiperiod returns
J. W. Taylor · 2000
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Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers
B. Zadrozny and C. Elkan · 2001
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Transforming classifier scores into accurate multiclass probability estimates
B. Zadrozny and C. Elkan · 2002
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Mondrian confidence machine
V. Vovk, D. Lindsay, I. Nouretdinov, and A. Gammerman · 2003
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Algorithmic learning in a random world
V. Vovk, A. Gammerman, and G. Shafer · 2005
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Quantile regression forests
N. Meinshausen · 2006
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On-line predictive linear regression
V. Vovk, I. Nouretdinov, and A. Gammerman · 2009
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Conditional validity of inductive conformal predictors
V. Vovk · 2012
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Distribution-free prediction bands for non-parametric regression
J. Lei and L. Wasserman · 2014
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On calibration of modern neural networks
C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger · 2017
Cited alongside, same era.
Y. Hechtlinger, B. Póczos, and L. Wasserman · 2018
Cited alongside, same era.
Distribution-free predictive inference for regression
J. Lei, M. G’Sell, A. Rinaldo, R. J. Tibshirani, and L. Wasserman · 2018
Cited alongside, same era.
Relaxed softmax: Efficient confidence auto-calibration for safe pedestrian detection
L. Neumann, A. Zisserman, and A. Vedaldi · 2018
Cited alongside, same era.
The limits of distribution-free conditional predictive inference
R. F. Barber, E. J. Candès, A. Ramdas, and R. J. Tibshirani · 2019
Cited alongside, same era.
Adaptive, distribution-free prediction intervals for deep neural networks
D. Kivaranovic, K. D. Johnson, and H. Leeb · 2019
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Nested conformal prediction and the generalized jackknife+
A. K. Kuchibhotla and A. K. Ramdas · 2019
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Verified uncertainty calibration
A. Kumar, P. S. Liang, and T. Ma · 2019
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Conformalized quantile regression
Y. Romano, E. Patterson, and E. J. Candès · 2019
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Least ambiguous set-valued classifiers with bounded error levels
M. Sadinle, J. Lei, and L. Wasserman · 2019
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V. Chernozhukov, K. Wüthrich, and Y. Zhu · 2019
Cited alongside, same era.
Predictive inference with the jackknife+
R. Foygel Barber, E. J. Candès, A. Ramdas, and R. J. Tibshirani · 2019
Cited alongside, same era.
Conformal prediction with localization
L. Guan · 2019
Cited alongside, same era.
Distribution-free conditional predictive bands using density estimators
R. Izbicki, G. T. Shimizu, and R. B. Stern · 2019
Cited alongside, same era.
J. Vaicenavicius, D. Widmann, C. Andersson, F. Lindsten, J. Roll, and T. B. Schön · 2019
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Knowing what you know: valid confidence sets in multiclass and multilabel prediction
M. Cauchois, S. Gupta, and J. Duchi · 2020
Closest in time.
With malice toward none: Assessing uncertainty via equalized coverage
Y. Romano, R. F. Barber, C. Sabatti, and E. Candès · 2020
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A comparison of some conformal quantile regression methods
M. Sesia and E. J. Candès · 2020
Closest in time.