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Agus Sudjianto
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2020 – today
- 2024
- [j14]Hengtao Zhang, Zebin Yang, Agus Sudjianto, Aijun Zhang:
A Sequential Stein's Method for Faster Training of Additive Index Models. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13941-13950 (2024) - [i23]Ying Li, Rahul Singh, Tarun Joshi, Agus Sudjianto:
Automatic Generation of Behavioral Test Cases For Natural Language Processing Using Clustering and Prompting. CoRR abs/2408.00161 (2024) - 2023
- [j13]Agus Sudjianto, Jinwen Qiu, Miaoqi Li, Jie Chen:
Linear iterative feature embedding: an ensemble framework for an interpretable model. Neural Comput. Appl. 35(13): 9657-9685 (2023) - [j12]Agus Sudjianto, Zebin Yang, Aijun Zhang:
Single-Index Model Tree. IEEE Trans. Knowl. Data Eng. 35(3): 3101-3114 (2023) - [i22]Shijie Cui, Agus Sudjianto, Aijun Zhang, Runze Li:
Enhancing Robustness of Gradient-Boosted Decision Trees through One-Hot Encoding and Regularization. CoRR abs/2304.13761 (2023) - [i21]Linwei Hu, Vijayan N. Nair, Agus Sudjianto, Aijun Zhang, Jie Chen:
Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons. CoRR abs/2305.15670 (2023) - 2022
- [i20]Vijayan N. Nair, Tianshu Feng, Linwei Hu, Zach Zhang, Jie Chen, Agus Sudjianto:
Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition. CoRR abs/2204.12365 (2022) - 2021
- [j11]Zebin Yang, Hengtao Zhang, Agus Sudjianto, Aijun Zhang:
An effective SteinGLM initialization scheme for training multi-layer feedforward sigmoidal neural networks. Neural Networks 139: 149-157 (2021) - [j10]Zebin Yang, Aijun Zhang, Agus Sudjianto:
GAMI-Net: An explainable neural network based on generalized additive models with structured interactions. Pattern Recognit. 120: 108192 (2021) - [j9]Zebin Yang, Aijun Zhang, Agus Sudjianto:
Enhancing Explainability of Neural Networks Through Architecture Constraints. IEEE Trans. Neural Networks Learn. Syst. 32(6): 2610-2621 (2021) - [i19]Agus Sudjianto, Jinwen Qiu, Miaoqi Li, Jie Chen:
Linear Iterative Feature Embedding: An Ensemble Framework for Interpretable Model. CoRR abs/2103.09983 (2021) - [i18]Nengfeng Zhou, Zach Zhang, Vijayan N. Nair, Harsh Singhal, Jie Chen, Agus Sudjianto:
Bias, Fairness, and Accountability with AI and ML Algorithms. CoRR abs/2105.06558 (2021) - [i17]Wei Zhao, Rahul Singh, Tarun Joshi, Agus Sudjianto, Vijayan N. Nair:
Self-interpretable Convolutional Neural Networks for Text Classification. CoRR abs/2105.08589 (2021) - [i16]Shaojie Xu, Joel Vaughan, Jie Chen, Agus Sudjianto, Vijayan N. Nair:
Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons. CoRR abs/2109.04244 (2021) - [i15]Agus Sudjianto, Aijun Zhang:
Designing Inherently Interpretable Machine Learning Models. CoRR abs/2111.01743 (2021) - [i14]Shaojie Xu, Joel Vaughan, Jie Chen, Aijun Zhang, Agus Sudjianto:
Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification. CoRR abs/2111.08922 (2021) - 2020
- [i13]Zebin Yang, Aijun Zhang, Agus Sudjianto:
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions. CoRR abs/2003.07132 (2020) - [i12]Jie Chen, Joel Vaughan, Vijayan N. Nair, Agus Sudjianto:
Adaptive Explainable Neural Networks (AxNNs). CoRR abs/2004.02353 (2020) - [i11]Zebin Yang, Hengtao Zhang, Agus Sudjianto, Aijun Zhang:
An Effective and Efficient Initialization Scheme for Multi-layer Feedforward Neural Networks. CoRR abs/2005.08027 (2020) - [i10]Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto:
Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms. CoRR abs/2007.14528 (2020) - [i9]Linwei Hu, Jie Chen, Joel Vaughan, Hanyu Yang, Kelly Wang, Agus Sudjianto, Vijayan N. Nair:
Supervised Machine Learning Techniques: An Overview with Applications to Banking. CoRR abs/2008.04059 (2020) - [i8]Rahul Singh, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto:
Model Robustness with Text Classification: Semantic-preserving adversarial attacks. CoRR abs/2008.05536 (2020) - [i7]Wei Zhao, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto:
SHAP values for Explaining CNN-based Text Classification Models. CoRR abs/2008.11825 (2020) - [i6]Agus Sudjianto, William Knauth, Rahul Singh, Zebin Yang, Aijun Zhang:
Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification. CoRR abs/2011.04041 (2020)
2010 – 2019
- 2019
- [i5]Zebin Yang, Aijun Zhang, Agus Sudjianto:
Enhancing Explainability of Neural Networks through Architecture Constraints. CoRR abs/1901.03838 (2019) - [i4]Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto:
Time Series Simulation by Conditional Generative Adversarial Net. CoRR abs/1904.11419 (2019) - 2018
- [i3]Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto:
Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP). CoRR abs/1806.00663 (2018) - [i2]Joel Vaughan, Agus Sudjianto, Erind Brahimi, Jie Chen, Vijayan N. Nair:
Explainable Neural Networks based on Additive Index Models. CoRR abs/1806.01933 (2018) - [i1]Xiaoyu Liu, Jie Chen, Vijayan N. Nair, Agus Sudjianto:
Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning. CoRR abs/1808.07216 (2018) - 2016
- [j8]Jonathan J. Forster, Matteo Buzzacchi, Agus Sudjianto, Risa Nagao:
Modelling credit grade migration in large portfolios using cumulative t-link transition models. Eur. J. Oper. Res. 254(3): 977-984 (2016) - 2010
- [j7]Agus Sudjianto, Sheela Nair, Ming Yuan, Aijun Zhang, Daniel A. Kern, Fernando Cela-Díaz:
Statistical Methods for Fighting Financial Crimes. Technometrics 52(1): 5-19 (2010)
2000 – 2009
- 2008
- [j6]Remco Chang, Alvin Lee, Mohammad Ghoniem, Robert Kosara, William Ribarsky, Jing Yang, Evan A. Suma, Caroline Ziemkiewicz, Daniel A. Kern, Agus Sudjianto:
Scalable and interactive visual analysis of financial wire transactions for fraud detection. Inf. Vis. 7(1): 63-76 (2008) - 2007
- [c3]Remco Chang, Mohammad Ghoniem, Robert Kosara, William Ribarsky, Jing Yang, Evan A. Suma, Caroline Ziemkiewicz, Daniel A. Kern, Agus Sudjianto:
WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions. IEEE VAST 2007: 155-162 - [c2]Agus Sudjianto, Fernando Cela-Díaz, Aijun Zhang, Ming Yuan:
Anomaly Detection in High-Dimensional Financial Databases. MLMTA 2007: 105-112 - 2005
- [j5]Runze Li, Agus Sudjianto:
Analysis of Computer Experiments Using Penalized Likelihood in Gaussian Kriging Models. Technometrics 47(2): 111-120 (2005) - 2004
- [j4]Agus Sudjianto:
Discussion. Technometrics 46(1): 23-24 (2004) - [j3]David Mease, Vijayan N. Nair, Agus Sudjianto:
Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies. Technometrics 46(2): 165-175 (2004)
1990 – 1999
- 1997
- [j2]Paul Watta, Agus Sudjianto:
Pattern Recognition And Neural Networks [Book Reviews]. IEEE Trans. Neural Networks 8(3): 815-816 (1997) - 1996
- [c1]Agus Sudjianto, Mohamad H. Hassoun, Gary S. Wasserman:
Extensions of principal component analysis for nonlinear feature extraction. ICNN 1996: 1433-1438 - 1995
- [j1]Agus Sudjianto, Mohamad H. Hassoun:
Statistical basis of nonlinear hebbian learning and application to clustering. Neural Networks 8(5): 707-715 (1995)
Coauthor Index
aka: Vijayan N. Nair
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