Sparse representations for multiple measurement vectors (MMV) in an over-complete dictionary. - Jie Chen 054; Xiaoming Huo (ICASSP (4), 2005)

Theoretical Results on Sparse Representations of Multiple-Measurement Vectors. - Jie Chen 054; Xiaoming Huo (IEEE Trans. Signal Process., 2006)

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)

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)

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)

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

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)

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study. - Alice J. Liu; Linwei Hu; Jie Chen 054; Vijayan N. Nair (CoRR, 2022)

Interpretable Feature Engineering for Time Series Predictors using Attention Networks. - Tianjie Wang; Jie Chen 054; Joel Vaughan; Vijayan N. Nair (CoRR, 2022)

Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models. - Linwei Hu; Jie Chen 054; Vijayan N. Nair (CoRR, 2022)

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)

Monotone Tree-Based GAMI Models by Adapting XGBoost. - Linwei Hu; Soroush Aramideh; Jie Chen 054; Vijayan N. Nair (CoRR, 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)