Giles Hooker

CoRR, 2024

Provably Stable Feature Rankings with SHAP and LIME.

[BibT_eX]

[DOI]

Jeremy Goldwasser

CoRR, 2024

2023

Considerations when learning additive explanations for black-box models.

[BibT_eX]

[DOI]

Mach. Learn., September, 2023

Stabilizing Estimates of Shapley Values with Control Variates.

[BibT_eX]

[DOI]

Jeremy Goldwasser

CoRR, 2023

2022

Selecting the derivative of a functional covariate in scalar-on-function regression.

[BibT_eX]

[DOI]

Han Lin Shang

Stat. Comput., 2022

Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution.

[BibT_eX]

[DOI]

Yichen Zhou

J. Mach. Learn. Res., 2022

Decision tree boosted varying coefficient models.

[BibT_eX]

[DOI]

Yichen Zhou

Data Min. Knowl. Discov., 2022

A Generic Approach for Statistical Stability in Model Distillation.

[BibT_eX]

[DOI]

Yunzhe Zhou

Peiru Xu

CoRR, 2022

The Infinitesimal Jackknife and Combinations of Models.

[BibT_eX]

[DOI]

Indrayudh Ghosal

Yunzhe Zhou

CoRR, 2022

2021

Unbiased Measurement of Feature Importance in Tree-Based Methods.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance.

[BibT_eX]

[DOI]

Siyu Zhou

Stat. Comput., 2021

V-statistics and Variance Estimation.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and Its Variance Estimate.

[BibT_eX]

[DOI]

Indrayudh Ghosal

J. Comput. Graph. Stat., 2021

Bridging Breiman's Brook: From Algorithmic Modeling to Statistical Learning.

[BibT_eX]

[DOI]

CoRR, 2021

S-LIME: Stabilized-LIME for Model Explanation.

[BibT_eX]

[DOI]

Fei Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Timing observations of diffusions.

[BibT_eX]

[DOI]

Aurya Javeed

Stat. Comput., 2020

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable.

[BibT_eX]

[DOI]

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models.

[BibT_eX]

[DOI]

Benjamin J. Lengerich

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Asymptotic Normality and Variance Estimation For Supervised Ensembles.

[BibT_eX]

[DOI]

CoRR, 2019

Please Stop Permuting Features: An Explanation and Alternatives.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Bootstrap bias corrections for ensemble methods.

[BibT_eX]

[DOI]

Stat. Comput., 2018

Experimental Design for Partially Observed Markov Decision Processes.

[BibT_eX]

[DOI]

Leifur Thorbergsson

SIAM/ASA J. Uncertain. Quantification, 2018

Asymptotic Properties for Methods Combining the Minimum Hellinger Distance Estimate and the Bayesian Nonparametric Density Estimate.

[BibT_eX]

[DOI]

Yuefeng Wu

Entropy, 2018

Approximation Trees: Statistical Stability in Model Distillation.

[BibT_eX]

[DOI]

Yichen Zhou

CoRR, 2018

Transparent Model Distillation.

[BibT_eX]

[DOI]

CoRR, 2018

Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation.

[BibT_eX]

[DOI]

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017

Functional principal component analysis of spatially correlated data.

[BibT_eX]

[DOI]

Chong Liu

Surajit Ray

Stat. Comput., 2017

Detecting Bias in Black-Box Models Using Transparent Model Distillation.

[BibT_eX]

[DOI]

CoRR, 2017

Machine Learning and the Future of Realism.

[BibT_eX]

[DOI]

Cliff Hooker

CoRR, 2017

Control Variates as a Variance Reduction Technique for Random Projections.

[BibT_eX]

[DOI]

Keegan Kang

Proceedings of the Pattern Recognition Applications and Methods, 2017

Random Projections with Control Variates.

[BibT_eX]

[DOI]

Keegan Kang

Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017

2016

Maximal autocorrelation functions in functional data analysis.

[BibT_eX]

[DOI]

Steven Roberts

Stat. Comput., 2016

Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable.

[BibT_eX]

[DOI]

Hui Fen Tan

Martin T. Wells

CoRR, 2016

Improving the recovery of principal components with semi-deterministic random projections.

[BibT_eX]

[DOI]

Keegan Kang

Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

2015

Restricted likelihood ratio tests for linearity in scalar-on-function regression.

[BibT_eX]

[DOI]

Mathew W. McLean

David Ruppert

Stat. Comput., 2015

Control Theory and Experimental Design in Diffusion Processes.

[BibT_eX]

[DOI]

Kevin K. Lin

Bruce Rogers

SIAM/ASA J. Uncertain. Quantification, 2015

2013

Accurate intelligible models with pairwise interactions.

[BibT_eX]

[DOI]

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012

Prediction-based regularization using data augmented regression.

[BibT_eX]

[DOI]

Saharon Rosset

Stat. Comput., 2012

Learned-loss boosting.

[BibT_eX]

[DOI]

James O. Ramsay

Comput. Stat. Data Anal., 2012

2004

Discovering additive structure in black box functions.

[BibT_eX]

[DOI]

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Diagnosing extrapolation: tree-based density estimation.

[BibT_eX]

[DOI]