Statistical basis of nonlinear hebbian learning and application to clustering. - Agus Sudjianto; Mohamad H. Hassoun (Neural Networks, 1995)

Extensions of principal component analysis for nonlinear feature extraction. - Agus Sudjianto; Mohamad H. Hassoun; Gary S. Wasserman (ICNN, 1996)

Pattern Recognition And Neural Networks [Book Reviews]. - Paul Watta; Agus Sudjianto (IEEE Trans. Neural Networks, 1997)

Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies. - David Mease; Vijayan N. Nair; Agus Sudjianto (Technometrics, 2004)

Discussion. - Agus Sudjianto (Technometrics, 2004)

Analysis of Computer Experiments Using Penalized Likelihood in Gaussian Kriging Models. - Runze Li 001; Agus Sudjianto (Technometrics, 2005)

WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions. - Remco Chang; Mohammad Ghoniem; Robert Kosara; William Ribarsky; Jing Yang 001; Evan A. Suma; Caroline Ziemkiewicz; Daniel A. Kern; Agus Sudjianto (IEEE VAST, 2007)

Anomaly Detection in High-Dimensional Financial Databases. - Agus Sudjianto; Fernando Cela-Díaz; Aijun Zhang; Ming Yuan 001 (MLMTA, 2007)

Scalable and interactive visual analysis of financial wire transactions for fraud detection. - Remco Chang; Alvin Lee; Mohammad Ghoniem; Robert Kosara; William Ribarsky; Jing Yang 001; Evan A. Suma; Caroline Ziemkiewicz; Daniel A. Kern; Agus Sudjianto (Inf. Vis., 2008)

Statistical Methods for Fighting Financial Crimes. - Agus Sudjianto; Sheela Nair; Ming Yuan 001; Aijun Zhang; Daniel A. Kern; Fernando Cela-Díaz (Technometrics, 2010)

Modelling credit grade migration in large portfolios using cumulative t-link transition models. - Jonathan J. Forster; Matteo Buzzacchi; Agus Sudjianto; Risa Nagao (Eur. J. Oper. Res., 2016)

Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP). - Linwei Hu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2018)

Explainable Neural Networks based on Additive Index Models. - Joel Vaughan; Agus Sudjianto; Erind Brahimi; Jie Chen 054; Vijayan N. Nair (CoRR, 2018)

Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning. - Xiaoyu Liu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2018)

Time Series Simulation by Conditional Generative Adversarial Net. - Rao Fu; Jie Chen 054; Shutian Zeng; Yiping Zhuang; Agus Sudjianto (CoRR, 2019)

Adaptive Explainable Neural Networks (AxNNs). - Jie Chen 054; Joel Vaughan; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

An Effective and Efficient Initialization Scheme for Multi-layer Feedforward Neural Networks. - Zebin Yang 001; Hengtao Zhang; Agus Sudjianto; Aijun Zhang (CoRR, 2020)

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms. - Linwei Hu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

Supervised Machine Learning Techniques: An Overview with Applications to Banking. - Linwei Hu; Jie Chen 054; Joel Vaughan; Hanyu Yang; Kelly Wang; Agus Sudjianto; Vijayan N. Nair (CoRR, 2020)

Model Robustness with Text Classification: Semantic-preserving adversarial attacks. - Rahul Singh; Tarun Joshi; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

SHAP values for Explaining CNN-based Text Classification Models. - Wei Zhao; Tarun Joshi; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification. - Agus Sudjianto; William Knauth; Rahul Singh; Zebin Yang 001; Aijun Zhang (CoRR, 2020)

Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model. - Agus Sudjianto; Jinwen Qiu; Miaoqi Li; Jie Chen 054 (CoRR, 2021)

Bias, Fairness, and Accountability with AI and ML Algorithms. - Nengfeng Zhou; Zach Zhang; Vijayan N. Nair; Harsh Singhal; Jie Chen 054; Agus Sudjianto (CoRR, 2021)

Self-interpretable Convolutional Neural Networks for Text Classification. - Wei Zhao; Rahul Singh; Tarun Joshi; Agus Sudjianto; Vijayan N. Nair (CoRR, 2021)

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons. - Shaojie Xu; Joel Vaughan; Jie Chen 054; Agus Sudjianto; Vijayan N. Nair (CoRR, 2021)

Designing Inherently Interpretable Machine Learning Models. - Agus Sudjianto; Aijun Zhang (CoRR, 2021)

Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification. - Shaojie Xu; Joel Vaughan; Jie Chen 054; Aijun Zhang; Agus Sudjianto (CoRR, 2021)

An effective SteinGLM initialization scheme for training multi-layer feedforward sigmoidal neural networks. - Zebin Yang 001; Hengtao Zhang; Agus Sudjianto; Aijun Zhang (Neural Networks, 2021)

GAMI-Net: An explainable neural network based on generalized additive models with structured interactions. - Zebin Yang 001; Aijun Zhang; Agus Sudjianto (Pattern Recognit., 2021)

Enhancing Explainability of Neural Networks Through Architecture Constraints. - Zebin Yang 001; Aijun Zhang; Agus Sudjianto (IEEE Trans. Neural Networks Learn. Syst., 2021)

Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition. - Vijayan N. Nair; Tianshu Feng; Linwei Hu; Zach Zhang; Jie Chen 054; Agus Sudjianto (CoRR, 2022)

Enhancing Robustness of Gradient-Boosted Decision Trees through One-Hot Encoding and Regularization. - Shijie Cui; Agus Sudjianto; Aijun Zhang; Runze Li (CoRR, 2023)

Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons. - Linwei Hu; Vijayan N. Nair; Agus Sudjianto; Aijun Zhang; Jie Chen 054 (CoRR, 2023)

Single-Index Model Tree. - Agus Sudjianto; Zebin Yang 001; Aijun Zhang (IEEE Trans. Knowl. Data Eng., 2023)

Linear iterative feature embedding: an ensemble framework for an interpretable model. - Agus Sudjianto; Jinwen Qiu; Miaoqi Li; Jie Chen 054 (Neural Comput. Appl., 2023)

Automatic Generation of Behavioral Test Cases For Natural Language Processing Using Clustering and Prompting. - Ying Li; Rahul Singh; Tarun Joshi; Agus Sudjianto (CoRR, 2024)

Model Validation Practice in Banking: A Structured Approach. - Agus Sudjianto; Aijun Zhang (CoRR, 2024)

Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification. - Andrew C. Pangia; Agus Sudjianto; Aijun Zhang; Taufiquar Khan (CoRR, 2024)

Inherently Interpretable Tree Ensemble Learning. - Zebin Yang 001; Agus Sudjianto; Xiaoming Li; Aijun Zhang (CoRR, 2024)

Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations. - Yueyang Shen; Agus Sudjianto; Arun Prakash R; Anwesha Bhattacharyya; Maorong Rao; Yaqun Wang; Joel Vaughan; Nengfeng Zhou (CoRR, 2024)

Human-Calibrated Automated Testing and Validation of Generative Language Models. - Agus Sudjianto; Aijun Zhang; Srinivas Neppalli; Tarun Joshi; Michal Malohlava (CoRR, 2024)

A Sequential Stein's Method for Faster Training of Additive Index Models. - Hengtao Zhang; Zebin Yang 001; Agus Sudjianto; Aijun Zhang (IEEE Trans. Neural Networks Learn. Syst., 2024)