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Vijay N. Nair
Person information
- affiliation: University of Michigan, Ann Arbor, MI, USA
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2020 – today
- 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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