Giles Hooker | DeepAI

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Fei Wang
189 publications
Rich Caruana
28 publications
Martin T. Wells
25 publications
Lucas Mentch
17 publications
Albert Gordo
14 publications
Sarah Tan
13 publications
Yichen Zhou
12 publications
Chun-Hao Chang
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Zi Ye
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Zhengze Zhou
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Skyler Seto
6 publications

∙ 11/22/2022

A Generic Approach for Reproducible Model Distillation

Model distillation has been a popular method for producing interpretable...

0 Yunzhe Zhou, et al. ∙

∙ 08/31/2022

The Infinitesimal Jackknife and Combinations of Models

The Infinitesimal Jackknife is a general method for estimating variances...

0 Indrayudh Ghosal, et al. ∙

∙ 06/15/2021

S-LIME: Stabilized-LIME for Model Explanation

An increasing number of machine learning models have been deployed in do...

0 Zhengze Zhou, et al. ∙

∙ 02/24/2021

Generalised Boosted Forests

This paper extends recent work on boosting random forests to model non-G...

15 Indrayudh Ghosal, et al. ∙

∙ 02/23/2021

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

In 2001, Leo Breiman wrote of a divide between "data modeling" and "algo...

0 Lucas Mentch, et al. ∙

∙ 11/25/2020

Generalized Single Index Models and Jensen Effects on Reproduction and Survival

Environmental variability often has substantial impacts on natural popul...

0 Zi Ye, et al. ∙

∙ 08/18/2020

Selecting the Derivative of a Functional Covariate in Scalar-on-Function Regression

This paper presents tests to formally choose between regression models u...

0 Giles Hooker, et al. ∙

∙ 12/02/2019

Asymptotic Normality and Variance Estimation For Supervised Ensembles

Ensemble methods based on bootstrapping have improved the predictive acc...

0 Zhengze Zhou, et al. ∙

∙ 11/12/2019

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

Recent methods for training generalized additive models (GAMs) with pair...

0 Benjamin Lengerich, et al. ∙

∙ 05/01/2019

Please Stop Permuting Features: An Explanation and Alternatives

This paper advocates against permute-and-predict (PaP) methods for inter...

0 Giles Hooker, et al. ∙

∙ 04/01/2019

Tree Boosted Varying Coefficient Models

This paper investigates the integration of gradient boosted decision tre...

0 Yichen Zhou, et al. ∙

∙ 03/12/2019

Unbiased Measurement of Feature Importance in Tree-Based Methods

We propose a modification that corrects for split-improvement variable i...

0 Zhengze Zhou, et al. ∙

∙ 01/07/2019

The Jensen Effect and Functional Single Index Models: Estimating the Ecological Implications of Nonlinear Reaction Norms

This paper develops tools to characterize how species are affected by en...

0 Zi Ye, et al. ∙

∙ 10/18/2018

Asymptotic Properties for Methods Combining Minimum Hellinger Distance Estimates and Bayesian Nonparametric Density Estimates

In frequentist inference, minimizing the Hellinger distance between a ke...

0 Yuefeng Wu, et al. ∙

∙ 08/22/2018

Approximation Trees: Statistical Stability in Model Distillation

This paper examines the stability of learned explanations for black-box ...

2 Yichen Zhou, et al. ∙

∙ 06/26/2018

Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution

This paper examines a novel gradient boosting framework for regression. ...

0 Yichen Zhou, et al. ∙

∙ 03/25/2018

Local Quadratic Estimation of the Curvature in a Functional Single Index Model

The nonlinear effects of environmental variability on species abundance ...

0 Zi Ye, et al. ∙

∙ 03/21/2018

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

In this paper we propose using the principle of boosting to reduce the b...

0 Indrayudh Ghosal, et al. ∙

∙ 01/26/2018

Transparent Model Distillation

Model distillation was originally designed to distill knowledge from a l...

0 Sarah Tan, et al. ∙

∙ 11/19/2017

A Double Parametric Bootstrap Test for Topic Models

Non-negative matrix factorization (NMF) is a technique for finding laten...

0 Skyler Seto, et al. ∙

∙ 10/26/2017

Statistical Inference on Tree Swallow Migrations, Using Random Forests

Species migratory patterns have typically been studied through individua...

0 Tim Coleman, et al. ∙

∙ 10/17/2017

Detecting Bias in Black-Box Models Using Transparent Model Distillation

Black-box risk scoring models permeate our lives, yet are typically prop...

0 Sarah Tan, et al. ∙

∙ 08/15/2017

Sparse Inverse Covariance Estimation for High-throughput microRNA Sequencing Data in the Poisson Log-Normal Graphical Model

We introduce the Poisson Log-Normal Graphical Model for count data, and ...

0 David Sinclair, et al. ∙

∙ 04/15/2017

Machine Learning and the Future of Realism

The preceding three decades have seen the emergence, rise, and prolifera...

0 Giles Hooker, et al. ∙

∙ 06/01/2015

Bootstrap Bias Corrections for Ensemble Methods

This paper examines the use of a residual bootstrap for bias correction ...

0 Giles Hooker, et al. ∙

∙ 04/25/2014

Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests

This work develops formal statistical inference procedures for machine l...

0 Lucas Mentch, et al. ∙