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11/22/2022
A Generic Approach for Reproducible Model Distillation
Model distillation has been a popular method for producing interpretable...
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08/31/2022
The Infinitesimal Jackknife and Combinations of Models
The Infinitesimal Jackknife is a general method for estimating variances...
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06/15/2021
S-LIME: Stabilized-LIME for Model Explanation
An increasing number of machine learning models have been deployed in do...
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02/24/2021
Generalised Boosted Forests
This paper extends recent work on boosting random forests to model non-G...
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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...
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11/25/2020
Generalized Single Index Models and Jensen Effects on Reproduction and Survival
Environmental variability often has substantial impacts on natural popul...
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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...
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12/02/2019
Asymptotic Normality and Variance Estimation For Supervised Ensembles
Ensemble methods based on bootstrapping have improved the predictive acc...
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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...
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05/01/2019
Please Stop Permuting Features: An Explanation and Alternatives
This paper advocates against permute-and-predict (PaP) methods for inter...
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04/01/2019
Tree Boosted Varying Coefficient Models
This paper investigates the integration of gradient boosted decision tre...
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03/12/2019
Unbiased Measurement of Feature Importance in Tree-Based Methods
We propose a modification that corrects for split-improvement variable i...
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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...
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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...
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08/22/2018
Approximation Trees: Statistical Stability in Model Distillation
This paper examines the stability of learned explanations for black-box ...
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06/26/2018
Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution
This paper examines a novel gradient boosting framework for regression. ...
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03/25/2018
Local Quadratic Estimation of the Curvature in a Functional Single Index Model
The nonlinear effects of environmental variability on species abundance ...
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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...
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01/26/2018
Transparent Model Distillation
Model distillation was originally designed to distill knowledge from a l...
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11/19/2017
A Double Parametric Bootstrap Test for Topic Models
Non-negative matrix factorization (NMF) is a technique for finding laten...
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10/26/2017
Statistical Inference on Tree Swallow Migrations, Using Random Forests
Species migratory patterns have typically been studied through individua...
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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...
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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 ...
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04/15/2017
Machine Learning and the Future of Realism
The preceding three decades have seen the emergence, rise, and prolifera...
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06/01/2015
Bootstrap Bias Corrections for Ensemble Methods
This paper examines the use of a residual bootstrap for bias correction ...
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04/25/2014
