Nandan Sudarsanam

A drop-out mechanism for active learning based on one-attribute heuristics
Active learning with human heuristics: an algorithm robust to labeling bias
Understanding the role of mobility in the recorded levels of violent crimes during COVID-19 pandemic: a case study of Tamil Nadu, India
Profitable market mechanism for platform-based aggregator taxi services
Counterfactual analysis of the impact of the first two waves of the COVID-19 pandemic on the reporting and registration of missing people in India
Crime registration and distress calls during COVID-19: two sides of the coin
Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic
Quantifying the maximum possible improvement in $2^{k}$ experiments
Relationship between mobility and road traffic injuries during COVID-19 pandemic—The role of attendant factors
Impact of COVID-19 pandemic on road safety in Tamil Nadu, India
An Active Learning Framework for Efficient Robust Policy Search
The Effect of COVID 19 on Crime
Learning With Limited Partial and Noisy Data
Inferring customer occupancy status in for-hire vehicles using PU Learning
Conducting Non-adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size
Rate of change analysis for interestingness measures
Optimal replicates for designed experiments under the online framework
Efficient-UCBV: An Almost Optimal Algorithm using Variance Estimates
Improved Insights on Financial Health through Partially Constrained Hidden Markov Model Clustering on Loan Repayment Data
A Partial Parameter HMM Based Clustering on Loan Repayment Data: Insights into Financial Behavior and Intent to Repay
Using Linear Stochastic Bandits to extend traditional offline Designed Experiments to online settings
Thresholding Bandits with Augmented UCB