Jie Chen

Affiliations:

Wells Fargo, Corporate Model Risk, San Francisco, CA, USA
Georgia Institute of Technology, Stewart School of Industrial and Systems Engineering, Atlanta, GA, USA (PhD)

According to our database¹, Jie Chen authored at least 20 papers between 2005 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2023

Linear iterative feature embedding: an ensemble framework for an interpretable model.

[BibT_eX]

[DOI]

Neural Comput. Appl., May, 2023

Monotone Tree-Based GAMI Models by Adapting XGBoost.

[BibT_eX]

[DOI]

CoRR, 2023

Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models.

[BibT_eX]

[DOI]

Linwei Hu

Jie Chen

Vijayan N. Nair

CoRR, 2022

Interpretable Feature Engineering for Time Series Predictors using Attention Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study.

[BibT_eX]

[DOI]

CoRR, 2022

Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification.

[BibT_eX]

[DOI]

CoRR, 2021

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons.

[BibT_eX]

[DOI]

CoRR, 2021

Bias, Fairness, and Accountability with AI and ML Algorithms.

[BibT_eX]

[DOI]

CoRR, 2021

Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Supervised Machine Learning Techniques: An Overview with Applications to Banking.

[BibT_eX]

[DOI]

CoRR, 2020

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

Adaptive Explainable Neural Networks (AxNNs).

[BibT_eX]

[DOI]

CoRR, 2020

2019

Time Series Simulation by Conditional Generative Adversarial Net.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Explainable Neural Networks based on Additive Index Models.

[BibT_eX]

[DOI]

CoRR, 2018

Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP).

[BibT_eX]

[DOI]

CoRR, 2018

2006

Theoretical Results on Sparse Representations of Multiple-Measurement Vectors.

[BibT_eX]

[DOI]

Jie Chen

Xiaoming Huo

IEEE Trans. Signal Process., 2006

2005

Sparse representations for multiple measurement vectors (MMV) in an over-complete dictionary.

[BibT_eX]

[DOI]

Jie Chen

Xiaoming Huo

Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Jie Chen

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