Optimal Sequential Selection of Secretaries. - Colin L. Mallows; Vijayan N. Nair; Larry A. Shepp; Yehuda Vardi (Math. Oper. Res., 1985)

Methods for Identifying Dispersion Effects in Unreplicated Factorial Experiments - A Critical Analysis and Proposed Strategies. - William A. Brenneman; Vijayan N. Nair (Technometrics, 2001)

Proportional Integral Derivative Charts for Process Monitoring. - Wei Jiang; Huaiqing Wu; Fugee Tsung; Vijayan N. Nair; Kwok-Leung Tsui (Technometrics, 2002)

Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies. - David Mease; Vijayan N. Nair; Agus Sudjianto (Technometrics, 2004)

Discussion. - Vijayan N. Nair; Xiao Wang 045 (Technometrics, 2004)

Local area network analysis using end-to-end delay tomography. - Earl Lawrence; George Michailidis; Vijay N. Nair (SIGMETRICS Perform. Evaluation Rev., 2005)

Extreme (X-)Testing With Binary Data and Applications to Reliability Demonstration. - David Mease; Vijayan N. Nair (Technometrics, 2006)

Statistical Aspects of the Analysis of Data Networks. - Lorraine Denby; Jim Landwehr; Colin L. Mallows; Jean Meloche; John Tuck; Bowei Xi; George Michailidis; Vijayan N. Nair (Technometrics, 2007)

Special Issue on Statistics in Information Technology. - Vijay N. Nair (Technometrics, 2007)

Graphical Estimators From Probability Plots With Right-Censored Data. - Anupap Somboonsavatdee; Vijayan N. Nair; Ananda Sen (Technometrics, 2007)

Bayesian Inference for Multivariate Ordinal Data Using Parameter Expansion. - Earl Lawrence; Derek Bingham; Chuanhai Liu; Vijayan N. Nair (Technometrics, 2008)

Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes. - Casey O. Diekman; Kohinoor Dasgupta; Vijay N. Nair; P. S. Sastry 001; K. P. Unnikrishnan (CoRR, 2009)

Predictive modeling of a radiative shock system. - 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; et al. (Reliab. Eng. Syst. Saf., 2011)

Noise Variable Settings in Robust Design Experiments. - Derek Bingham; Vijayan N. Nair (Technometrics, 2012)

Discovering Functional Neuronal Connectivity from Serial Patterns in Spike Train Data. - Casey O. Diekman; Kohinoor Dasgupta; Vijay N. Nair; K. P. Unnikrishnan (Neural Comput., 2014)

Editorial. - Yong Chen; V. Roshan Joseph; Yu Ding 002; Vijay N. Nair (Technometrics, 2015)

3D stacked embedded component system-in-package for wearable electronic devices. - Vijay N. Nair; L. Krishnamurthy; Johanna Swan; A. Essaian; Torrey W. Frank; Michael Bynum 002 (RWS, 2017)

Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP). - Linwei Hu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2018)

Explainable Neural Networks based on Additive Index Models. - Joel Vaughan; Agus Sudjianto; Erind Brahimi; Jie Chen 054; Vijayan N. Nair (CoRR, 2018)

Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning. - Xiaoyu Liu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2018)

Adaptive Explainable Neural Networks (AxNNs). - Jie Chen 054; Joel Vaughan; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms. - Linwei Hu; Jie Chen 054; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

Supervised Machine Learning Techniques: An Overview with Applications to Banking. - Linwei Hu; Jie Chen 054; Joel Vaughan; Hanyu Yang; Kelly Wang; Agus Sudjianto; Vijayan N. Nair (CoRR, 2020)

Model Robustness with Text Classification: Semantic-preserving adversarial attacks. - Rahul Singh; Tarun Joshi; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

SHAP values for Explaining CNN-based Text Classification Models. - Wei Zhao; Tarun Joshi; Vijayan N. Nair; Agus Sudjianto (CoRR, 2020)

Recent Trends in the Use of Deep Learning Models for Grammar Error Handling. - Mina Naghshnejad; Tarun Joshi; Vijayan N. Nair (CoRR, 2020)

Bias, Fairness, and Accountability with AI and ML Algorithms. - Nengfeng Zhou; Zach Zhang; Vijayan N. Nair; Harsh Singhal; Jie Chen 054; Agus Sudjianto (CoRR, 2021)

Self-interpretable Convolutional Neural Networks for Text Classification. - Wei Zhao; Rahul Singh; Tarun Joshi; Agus Sudjianto; Vijayan N. Nair (CoRR, 2021)

Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons. - Shaojie Xu; Joel Vaughan; Jie Chen 054; Agus Sudjianto; Vijayan N. Nair (CoRR, 2021)

Document Automation Architectures and Technologies: A Survey. - Mohammad Ahmadi Achachlouei; Omkar Patil; Tarun Joshi; Vijayan N. Nair (CoRR, 2021)

Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition. - Vijayan N. Nair; Tianshu Feng; Linwei Hu; Zach Zhang; Jie Chen 054; Agus Sudjianto (CoRR, 2022)

Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study. - Alice J. Liu; Linwei Hu; Jie Chen 054; Vijayan N. Nair (CoRR, 2022)

Interpretable Feature Engineering for Time Series Predictors using Attention Networks. - Tianjie Wang; Jie Chen 054; Joel Vaughan; Vijayan N. Nair (CoRR, 2022)

Quantifying Inherent Randomness in Machine Learning Algorithms. - Soham Raste; Rahul Singh; Joel Vaughan; Vijayan N. Nair (CoRR, 2022)

Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models. - Linwei Hu; Jie Chen 054; Vijayan N. Nair (CoRR, 2022)

Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights. - Tianshu Feng; Zhipu Zhou; Tarun Joshi; Vijayan N. Nair (CoRR, 2022)

Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation. - Anwesha Bhattacharyya; Joel Vaughan; Vijayan N. Nair (CoRR, 2022)

Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons. - Linwei Hu; Vijayan N. Nair; Agus Sudjianto; Aijun Zhang; Jie Chen 054 (CoRR, 2023)

Document Automation Architectures: Updated Survey in Light of Large Language Models. - Mohammad Ahmadi Achachlouei; Omkar Patil; Tarun Joshi; Vijayan N. Nair (CoRR, 2023)

Monotone Tree-Based GAMI Models by Adapting XGBoost. - Linwei Hu; Soroush Aramideh; Jie Chen 054; Vijayan N. Nair (CoRR, 2023)

Assessing Robustness of Machine Learning Models using Covariate Perturbations. - Arun Prakash R; Anwesha Bhattacharyya; Joel Vaughan; Vijayan N. Nair (CoRR, 2024)

Cross Spline Net and a Unified World. - Linwei Hu; Ye Jin Choi; Vijayan N. Nair (CoRR, 2024)