Nandan Sudarsanam
Nandan Sudarsanam
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Regularities in data from factorial experiments
X Li, N Sudarsanam, DD Frey
Complexity 11 (5), 32-45, 2006
Thresholding bandits with augmented ucb
S Mukherjee, KP Naveen, N Sudarsanam, B Ravindran
arXiv preprint arXiv:1704.02281, 2017
An adaptive one-factor-at-a-time method for robust parameter design: Comparison with crossed arrays via case studies
DD Frey, N Sudarsanam
Efficient-ucbv: An almost optimal algorithm using variance estimates
S Mukherjee, KP Naveen, N Sudarsanam, B Ravindran
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Rate of change analysis for interestingness measures
N Sudarsanam, N Kumar, A Sharma, B Ravindran
Knowledge and Information Systems 62 (1), 239-258, 2020
An adaptive one-factor-at-a-time method for robust parameter design: comparison with crossed arrays via case studies
DD Frey, N Sudarsanam, JB Persons
International Design Engineering Technical Conferences and Computers and …, 2006
Improved insights on financial health through partially constrained hidden markov model clustering on loan repayment data
DJ Philip, N Sudarsanam, B Ravindran
ACM SIGMIS Database: the DATABASE for Advances in Information Systems 49 (3 …, 2018
Using linear stochastic bandits to extend traditional offline designed experiments to online settings
N Sudarsanam, B Ravindran
Computers & Industrial Engineering 115, 471-485, 2018
Using ensemble techniques to advance adaptive one‐factor‐at‐a‐time experimentation
N Sudarsanam, DD Frey
Quality and Reliability Engineering International 27 (7), 947-957, 2011
Linear Bandit algorithms using the Bootstrap
N Sudarsanam, B Ravindran
arXiv preprint arXiv:1605.01185, 2016
Impact of COVID-19 pandemic on road safety in Tamil Nadu, India
K Paramasivan, N Sudarsanam
International journal of injury control and safety promotion 29 (2), 265-277, 2022
Optimal replicates for designed experiments under the online framework
N Sudarsanam, B Pitchai Kannu, DD Frey
Research in Engineering Design 30 (3), 363-379, 2019
Quantifying and predicting prepayments in the microfinance environment
N Sudarsanam, DJ Philip
NSE-IFMR Finance Foundation Financial Deepening and Household Finance …, 2016
An Active Learning Framework for Efficient Robust Policy Search
SK Narayanaswami, N Sudarsanam, B Ravindran
5th Joint International Conference on Data Science & Management of Data (9th …, 2022
A partial parameter HMM based clustering on loan repayment data: Insights into financial behavior and intent to repay
D Philip, N Sudarsanam, B Ravindran
Proceedings of the 51st Hawaii International Conference on System Sciences, 2018
Quantifying the maximum possible improvement in 2 k experiments
N Sudarsanam, A Kumar, DD Frey
Research in Engineering Design, 1-18, 2022
Relationship between mobility and road traffic injuries during COVID-19 pandemic—The role of attendant factors
K Paramasivan, R Subburaj, VM Sharma, N Sudarsanam
PloS one 17 (5), e0268190, 2022
A Decision-Making Framework for Entrepreneurial Venture in Emerging Economies
SB Kumar, N Sudarsanam
International Journal of Global Business and Competitiveness, 1-13, 2022
Crime registration and distress calls during COVID-19: two sides of the coin
K Paramasivan, N Sudarsanam, S Vellaichamy, KK Norris, R Subburaj
Policing and Society, 1-22, 2022
Designing Dynamic Interventions to Improve Adherence in Pediatric Long-Term Treatment–The Role of Perceived Value of the Physician by Primary Caregivers
K Venkatraman, V Vijayalakshmi, N Sudarsanam, A Manoharan
Health Communication 36 (14), 1825-1840, 2021
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