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ORCIDVijay N. Nair
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- affiliation: University of Michigan, Ann Arbor, MI, USA
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2020 – today
- 2024
[i25]Arun Prakash R, Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair:
Assessing Robustness of Machine Learning Models using Covariate Perturbations. CoRR abs/2408.01300 (2024)- 2023
- [i24]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) - [i23]Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi, Vijayan N. Nair:
Document Automation Architectures: Updated Survey in Light of Large Language Models. CoRR abs/2308.09341 (2023) - [i22]Linwei Hu, Soroush Aramideh, Jie Chen, Vijayan N. Nair:
Monotone Tree-Based GAMI Models by Adapting XGBoost. CoRR abs/2309.02426 (2023) - 2022
- [i21]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) - [i20]Alice J. Liu, Linwei Hu, Jie Chen, Vijayan N. Nair:
Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study. CoRR abs/2204.12868 (2022) - [i19]Tianjie Wang, Jie Chen, Joel Vaughan, Vijayan N. Nair:
Interpretable Feature Engineering for Time Series Predictors using Attention Networks. CoRR abs/2205.12723 (2022) - [i18]Soham Raste, Rahul Singh, Joel Vaughan, Vijayan N. Nair:
Quantifying Inherent Randomness in Machine Learning Algorithms. CoRR abs/2206.12353 (2022) - [i17]Linwei Hu, Jie Chen, Vijayan N. Nair:
Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models. CoRR abs/2207.06950 (2022) - [i16]Tianshu Feng, Zhipu Zhou, Tarun Joshi, Vijayan N. Nair:
Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights. CoRR abs/2208.06096 (2022) - [i15]Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair:
Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation. CoRR abs/2211.08536 (2022) - 2021
- [i14]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) - [i13]Wei Zhao, Rahul Singh, Tarun Joshi, Agus Sudjianto, Vijayan N. Nair:
Self-interpretable Convolutional Neural Networks for Text Classification. CoRR abs/2105.08589 (2021) - [i12]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) - [i11]Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi, Vijayan N. Nair:
Document Automation Architectures and Technologies: A Survey. CoRR abs/2109.11603 (2021) - 2020
- [i10]Jie Chen, Joel Vaughan, Vijayan N. Nair, Agus Sudjianto:
Adaptive Explainable Neural Networks (AxNNs). CoRR abs/2004.02353 (2020) - [i9]Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto:
Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms. CoRR abs/2007.14528 (2020) - [i8]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) - [i7]Rahul Singh, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto:
Model Robustness with Text Classification: Semantic-preserving adversarial attacks. CoRR abs/2008.05536 (2020) - [i6]Wei Zhao, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto:
SHAP values for Explaining CNN-based Text Classification Models. CoRR abs/2008.11825 (2020) - [i5]Mina Naghshnejad, Tarun Joshi, Vijayan N. Nair:
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling. CoRR abs/2009.02358 (2020)
2010 – 2019
- 2018
- [i4]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) - [i3]Joel Vaughan, Agus Sudjianto, Erind Brahimi, Jie Chen, Vijayan N. Nair:
Explainable Neural Networks based on Additive Index Models. CoRR abs/1806.01933 (2018) - [i2]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) - 2017
- [c1]Vijay N. Nair, L. Krishnamurthy, Johanna Swan, A. Essaian, Torrey W. Frank, Michael Bynum
:
3D stacked embedded component system-in-package for wearable electronic devices. RWS 2017: 108-110 - 2015
- [j15]Yong Chen, V. Roshan Joseph, Yu Ding, Vijay N. Nair:
Editorial. Technometrics 57(3): 303-304 (2015) - 2014
- [j14]Casey O. Diekman, Kohinoor Dasgupta, Vijay N. Nair, K. P. Unnikrishnan:
Discovering Functional Neuronal Connectivity from Serial Patterns in Spike Train Data. Neural Comput. 26(7): 1263-1297 (2014) - 2012
- [j13]Derek Bingham, Vijayan N. Nair:
Noise Variable Settings in Robust Design Experiments. Technometrics 54(4): 388-397 (2012) - 2011
- [j12]James Paul Holloway, Derek Bingham, Chuan-Chih Chou, Forrest Doss, R. Paul Drake, Bruce Fryxell, Michael Grosskopf, Bart van der Holst, Bani K. Mallick, Ryan G. McClarren, Ashin Mukherjee, Vijay N. Nair, Kenneth G. Powell, Duchwan Ryu, Igor V. Sokolov, Gábor Tóth, Zhanyang Zhang:
Predictive modeling of a radiative shock system. Reliab. Eng. Syst. Saf. 96(9): 1184-1193 (2011)
2000 – 2009
- 2009
- [i1]Casey O. Diekman, Kohinoor Dasgupta, Vijay N. Nair, P. S. Sastry, K. P. Unnikrishnan:
Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes. CoRR abs/0902.3725 (2009) - 2008
- [j11]Earl Lawrence, Derek Bingham, Chuanhai Liu, Vijayan N. Nair:
Bayesian Inference for Multivariate Ordinal Data Using Parameter Expansion. Technometrics 50(2): 182-191 (2008) - 2007
- [j10]Vijay N. Nair:
Special Issue on Statistics in Information Technology. Technometrics 49(3): 236 (2007) - [j9]Lorraine Denby, Jim Landwehr, Colin L. Mallows, Jean Meloche, John Tuck, Bowei Xi, George Michailidis, Vijayan N. Nair:
Statistical Aspects of the Analysis of Data Networks. Technometrics 49(3): 318-334 (2007) - [j8]Anupap Somboonsavatdee, Vijayan N. Nair, Ananda Sen:
Graphical Estimators From Probability Plots With Right-Censored Data. Technometrics 49(4): 420-429 (2007) - 2006
- [j7]David Mease, Vijayan N. Nair:
Extreme (X-)Testing With Binary Data and Applications to Reliability Demonstration. Technometrics 48(3): 399-410 (2006) - 2005
- [j6]Earl Lawrence, George Michailidis, Vijay N. Nair:
Local area network analysis using end-to-end delay tomography. SIGMETRICS Perform. Evaluation Rev. 33(3): 39-45 (2005) - 2004
- [j5]Vijayan N. Nair, Xiao Wang:
Discussion. Technometrics 46(1): 19-23 (2004) - [j4]David Mease, Vijayan N. Nair, Agus Sudjianto:
Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies. Technometrics 46(2): 165-175 (2004) - 2002
- [j3]Wei Jiang, Huaiqing Wu, Fugee Tsung, Vijayan N. Nair, Kwok-Leung Tsui:
Proportional Integral Derivative Charts for Process Monitoring. Technometrics 44(3): 205-214 (2002) - 2001
- [j2]William A. Brenneman, Vijayan N. Nair:
Methods for Identifying Dispersion Effects in Unreplicated Factorial Experiments - A Critical Analysis and Proposed Strategies. Technometrics 43(4): 388-405 (2001)
1980 – 1989
- 1985
- [j1]Colin L. Mallows, Vijayan N. Nair, Larry A. Shepp, Yehuda Vardi:
Optimal Sequential Selection of Secretaries. Math. Oper. Res. 10(4): 709-715 (1985)
Coauthor Index
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