Vijayan N. Nair

Publication Activity (10 Years)

Years Active: 1985-2023
Publications (10 Years): 23

Top Topics

Machine Learning

Text Classification

Learning Algorithm

Top Venues

Publications

Linwei Hu, Vijayan N. Nair, Agus Sudjianto, Aijun Zhang, Jie Chen
Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons. CoRR (2023)
Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi, Vijayan N. Nair
Document Automation Architectures: Updated Survey in Light of Large Language Models. CoRR (2023)
Linwei Hu, Soroush Aramideh, Jie Chen, Vijayan N. Nair
Monotone Tree-Based GAMI Models by Adapting XGBoost. CoRR (2023)
Tianshu Feng, Zhipu Zhou, Tarun Joshi, Vijayan N. Nair
Comparing Baseline Shapley and Integrated Gradients for Local Explanation: Some Additional Insights. CoRR (2022)
Alice J. Liu, Linwei Hu, Jie Chen, Vijayan N. Nair
Performance and Interpretability Comparisons of Supervised Machine Learning Algorithms: An Empirical Study. CoRR (2022)
Tianjie Wang, Jie Chen, Joel Vaughan, Vijayan N. Nair
Interpretable Feature Engineering for Time Series Predictors using Attention Networks. CoRR (2022)
Vijayan N. Nair, Tianshu Feng, Linwei Hu, Zach Zhang, Jie Chen, Agus Sudjianto
Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition. CoRR (2022)
Linwei Hu, Jie Chen, Vijayan N. Nair
Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models. CoRR (2022)
Soham Raste, Rahul Singh, Joel Vaughan, Vijayan N. Nair
Quantifying Inherent Randomness in Machine Learning Algorithms. CoRR (2022)
Anwesha Bhattacharyya, Joel Vaughan, Vijayan N. Nair
Behavior of Hyper-Parameters for Selected Machine Learning Algorithms: An Empirical Investigation. CoRR (2022)
Wei Zhao, Rahul Singh, Tarun Joshi, Agus Sudjianto, Vijayan N. Nair
Self-interpretable Convolutional Neural Networks for Text Classification. CoRR (2021)
Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi, Vijayan N. Nair
Document Automation Architectures and Technologies: A Survey. CoRR (2021)
Shaojie Xu, Joel Vaughan, Jie Chen, Agus Sudjianto, Vijayan N. Nair
Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons. CoRR (2021)
Nengfeng Zhou, Zach Zhang, Vijayan N. Nair, Harsh Singhal, Jie Chen, Agus Sudjianto
Bias, Fairness, and Accountability with AI and ML Algorithms. CoRR (2021)
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 (2020)
Jie Chen, Joel Vaughan, Vijayan N. Nair, Agus Sudjianto
Adaptive Explainable Neural Networks (AxNNs). CoRR (2020)
Rahul Singh, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto
Model Robustness with Text Classification: Semantic-preserving adversarial attacks. CoRR (2020)
Wei Zhao, Tarun Joshi, Vijayan N. Nair, Agus Sudjianto
SHAP values for Explaining CNN-based Text Classification Models. CoRR (2020)
Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto
Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms. CoRR (2020)
Mina Naghshnejad, Tarun Joshi, Vijayan N. Nair
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling. CoRR (2020)
Xiaoyu Liu, Jie Chen, Vijayan N. Nair, Agus Sudjianto
Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning. CoRR (2018)
Joel Vaughan, Agus Sudjianto, Erind Brahimi, Jie Chen, Vijayan N. Nair
Explainable Neural Networks based on Additive Index Models. CoRR (2018)
Linwei Hu, Jie Chen, Vijayan N. Nair, Agus Sudjianto
Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP). CoRR (2018)
Derek Bingham, Vijayan N. Nair
Noise Variable Settings in Robust Design Experiments. Technometrics 54 (4) (2012)
Earl Lawrence, Derek Bingham, Chuanhai Liu, Vijayan N. Nair
Bayesian Inference for Multivariate Ordinal Data Using Parameter Expansion. Technometrics 50 (2) (2008)
Anupap Somboonsavatdee, Vijayan N. Nair, Ananda Sen
Graphical Estimators From Probability Plots With Right-Censored Data. Technometrics 49 (4) (2007)
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) (2007)
David Mease, Vijayan N. Nair
Extreme (X-)Testing With Binary Data and Applications to Reliability Demonstration. Technometrics 48 (3) (2006)
David Mease, Vijayan N. Nair, Agus Sudjianto
Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies. Technometrics 46 (2) (2004)
Vijayan N. Nair, Xiao Wang
Discussion. Technometrics 46 (1) (2004)
Wei Jiang, Huaiqing Wu, Fugee Tsung, Vijayan N. Nair, Kwok-Leung Tsui
Proportional Integral Derivative Charts for Process Monitoring. Technometrics 44 (3) (2002)
William A. Brenneman, Vijayan N. Nair
Methods for Identifying Dispersion Effects in Unreplicated Factorial Experiments - A Critical Analysis and Proposed Strategies. Technometrics 43 (4) (2001)
Colin L. Mallows, Vijayan N. Nair, Larry A. Shepp, Yehuda Vardi
Optimal Sequential Selection of Secretaries. Math. Oper. Res. 10 (4) (1985)