Giles Hooker

According to our database1, Giles Hooker authored at least 28 papers between 2004 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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Bibliography

2020
Timing observations of diffusions.
Stat. Comput., 2020

Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Asymptotic Normality and Variance Estimation For Supervised Ensembles.
CoRR, 2019

Please Stop Permuting Features: An Explanation and Alternatives.
CoRR, 2019

Unbiased Measurement of Feature Importance in Tree-Based Methods.
CoRR, 2019

2018
Bootstrap bias corrections for ensemble methods.
Stat. Comput., 2018

Experimental Design for Partially Observed Markov Decision Processes.
SIAM/ASA J. Uncertain. Quantification, 2018

Asymptotic Properties for Methods Combining the Minimum Hellinger Distance Estimate and the Bayesian Nonparametric Density Estimate.
Entropy, 2018

Approximation Trees: Statistical Stability in Model Distillation.
CoRR, 2018

Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its Variance Estimate.
CoRR, 2018

Transparent Model Distillation.
CoRR, 2018

Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017
Functional principal component analysis of spatially correlated data.
Stat. Comput., 2017

Detecting Bias in Black-Box Models Using Transparent Model Distillation.
CoRR, 2017

Machine Learning and the Future of Realism.
CoRR, 2017

Control Variates as a Variance Reduction Technique for Random Projections.
Proceedings of the Pattern Recognition Applications and Methods, 2017

Random Projections with Control Variates.
Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017

2016
Maximal autocorrelation functions in functional data analysis.
Stat. Comput., 2016

Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests.
J. Mach. Learn. Res., 2016

Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable.
CoRR, 2016

Improving the recovery of principal components with semi-deterministic random projections.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

2015
Restricted likelihood ratio tests for linearity in scalar-on-function regression.
Stat. Comput., 2015

Control Theory and Experimental Design in Diffusion Processes.
SIAM/ASA J. Uncertain. Quantification, 2015

2013
Accurate intelligible models with pairwise interactions.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012
Prediction-based regularization using data augmented regression.
Stat. Comput., 2012

Learned-loss boosting.
Comput. Stat. Data Anal., 2012

2004
Discovering additive structure in black box functions.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Diagnosing extrapolation: tree-based density estimation.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004


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