Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model. - Narayanan Unny Edakunni; Stefan Schaal; Sethu Vijayakumar (IJCAI, 2007)

Modeling UCS as a mixture of experts. - Narayanan Unny Edakunni; Tim Kovacs; Gavin Brown 001; James A. R. Marshall (GECCO, 2009)

Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors. - Narayanan Unny Edakunni; Sethu Vijayakumar (MCS, 2009)

Online, GA based mixture of experts: a probabilistic model of ucs. - Narayanan Unny Edakunni; Gavin Brown 001; Tim Kovacs (GECCO, 2011)

Accuracy exponentiation in UCS and its effect on voting margins. - Tim Kovacs; Narayanan Unny Edakunni; Gavin Brown 001 (GECCO, 2011)

Boosting as a Product of Experts. - Narayanan Unny Edakunni; Gary Brown; Tim Kovacs (UAI, 2011)

Beyond Fano's inequality: bounds on the optimal F-score, BER, and cost-sensitive risk and their implications. - Ming-Jie Zhao; Narayanan Unny Edakunni; Adam Craig Pocock; Gavin Brown 001 (J. Mach. Learn. Res., 2013)

Probabilistic Dependency Networks for Prediction and Diagnostics. - Narayanan Unny Edakunni; Aditi Raghunathan; Abhishek Tripathi; John Handley; Frédéric Roulland (CoRR, 2015)

Cost-sensitive boosting algorithms: Do we really need them? - Nikolaos Nikolaou; Narayanan Unny Edakunni; Meelis Kull; Peter A. Flach; Gavin Brown 001 (Mach. Learn., 2016)

FairXGBoost: Fairness-aware Classification in XGBoost. - Srinivasan Ravichandran; Drona Khurana; Bharath Venkatesh; Narayanan Unny Edakunni (CoRR, 2020)

Accurate and Intuitive Contextual Explanations using Linear Model Trees. - Aditya Lahiri; Narayanan Unny Edakunni (CoRR, 2020)

Statistical Guarantees for Fairness Aware Plug-In Algorithms. - Drona Khurana; Srinivasan Ravichandran; Sparsh Jain; Narayanan Unny Edakunni (CoRR, 2021)

Simple is better: Making Decision Trees faster using random sampling. - Vignesh Nanda Kumar; Narayanan Unny Edakunni (CoRR, 2021)

Explaining Drift using Shapley Values. - Narayanan Unny Edakunni; Utkarsh Tekriwal; Anukriti Jain (CoRR, 2024)