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09/05/2023
Monotone Tree-Based GAMI Models by Adapting XGBoost
Recent papers have used machine learning architecture to fit low-order f...
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08/18/2023
Document Automation Architectures: Updated Survey in Light of Large Language Models
This paper surveys the current state of the art in document automation (...
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07/26/2023
Using Markov Boundary Approach for Interpretable and Generalizable Feature Selection
Predictive power and generalizability of models depend on the quality of...
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05/25/2023
Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons
In the early days of machine learning (ML), the emphasis was on developi...
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11/15/2022
Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation
Hyper-parameters (HPs) are an important part of machine learning (ML) mo...
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08/12/2022
Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights
There are many different methods in the literature for local explanation...
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07/14/2022
Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models
Low-order functional ANOVA (fANOVA) models have been rediscovered in the...
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05/23/2022
Interpretable Feature Engineering for Time Series Predictors using Attention Networks
Regression problems with time-series predictors are common in banking an...
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04/27/2022
Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study
This paper compares the performances of three supervised machine learnin...
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04/26/2022
Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition
When a financial institution declines an application for credit, an adve...
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09/23/2021
Document Automation Architectures and Technologies: A Survey
This paper surveys the current state of the art in document automation (...
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05/18/2021
Self-interpretable Convolutional Neural Networks for Text Classification
Deep learning models for natural language processing (NLP) are inherentl...
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05/13/2021
Bias, Fairness, and Accountability with AI and ML Algorithms
The advent of AI and ML algorithms has led to opportunities as well as c...
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09/04/2020
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling
Grammar error handling (GEH) is an important topic in natural language p...
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08/26/2020
SHAP values for Explaining CNN-based Text Classification Models
Deep neural networks are increasingly used in natural language processin...
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08/12/2020
Model Robustness with Text Classification: Semantic-preserving adversarial attacks
We propose algorithms to create adversarial attacks to assess model robu...
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07/28/2020
Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms
Supervised Machine Learning (SML) algorithms, such as Gradient Boosting,...
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04/05/2020
Adaptive Explainable Neural Networks (AxNNs)
While machine learning techniques have been successfully applied in seve...
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06/05/2018
Explainable Neural Networks based on Additive Index Models
Machine Learning algorithms are increasingly being used in recent years ...
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06/02/2018