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 17 papers between 2005 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2023
Linear iterative feature embedding: an ensemble framework for an interpretable model.
Neural Comput. Appl., May, 2023

2022
Interpretable Feature Engineering for Time Series Predictors using Attention Networks.
CoRR, 2022

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study.
CoRR, 2022

Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition.
CoRR, 2022

2021
Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification.
CoRR, 2021

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons.
CoRR, 2021

Bias, Fairness, and Accountability with AI and ML Algorithms.
CoRR, 2021

Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model.
CoRR, 2021

2020
Supervised Machine Learning Techniques: An Overview with Applications to Banking.
CoRR, 2020

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms.
CoRR, 2020

Adaptive Explainable Neural Networks (AxNNs).
CoRR, 2020

2019
Time Series Simulation by Conditional Generative Adversarial Net.
CoRR, 2019

2018
Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning.
CoRR, 2018

Explainable Neural Networks based on Additive Index Models.
CoRR, 2018

Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP).
CoRR, 2018

2006
Theoretical Results on Sparse Representations of Multiple-Measurement Vectors.
IEEE Trans. Signal Process., 2006

2005
Sparse representations for multiple measurement vectors (MMV) in an over-complete dictionary.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005


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