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Nandan Sudarsanam
Nandan Sudarsanam
Professor, Department of Data Science and AI, Indian Institute of Technology Madras
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Cited by
Cited by
Year
Regularities in data from factorial experiments
X Li, N Sudarsanam, DD Frey
Complexity 11 (5), 32-45, 2006
1522006
Thresholding bandits with augmented ucb
S Mukherjee, KP Naveen, N Sudarsanam, B Ravindran
arXiv preprint arXiv:1704.02281, 2017
302017
An adaptive one-factor-at-a-time method for robust parameter design: Comparison with crossed arrays via case studies
DD Frey, N Sudarsanam
172008
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
152018
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
102022
Rate of change analysis for interestingness measures
N Sudarsanam, N Kumar, A Sharma, B Ravindran
Knowledge and Information Systems 62 (1), 239-258, 2020
102020
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
102018
Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic
K Paramasivan, R Subburaj, S Jaiswal, N Sudarsanam
Humanities and Social Sciences Communications 9 (1), 1-14, 2022
82022
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
72022
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
72006
Using linear stochastic bandits to extend traditional offline designed experiments to online settings
N Sudarsanam, B Ravindran
Computers & Industrial Engineering 115, 471-485, 2018
62018
A decision-making framework for entrepreneurial venture in emerging economies
SB Kumar, N Sudarsanam
International Journal of Global Business and Competitiveness 17 (1), 11-23, 2022
52022
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
52011
Profitable market mechanism for platform-based aggregator taxi services
S Rammohan, RR Marathe, N Sudarsanam
Transportation Research Interdisciplinary Perspectives 16, 100687, 2022
42022
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 32 (9), 1124-1145, 2022
42022
Linear Bandit algorithms using the Bootstrap
N Sudarsanam, B Ravindran
arXiv preprint arXiv:1605.01185, 2016
32016
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
22019
Quantifying and predicting prepayments in the microfinance environment
N Sudarsanam, DJ Philip
NSE-IFMR Finance Foundation Financial Deepening and Household Finance …, 2016
22016
Recent advancements in revenue management of taxi services: a systematic review and research agenda
S Rammohan, RR Marathe, N Sudarsanam
Management Review Quarterly 74 (2), 1029-1055, 2024
12024
An Active Learning Framework for Efficient Robust Policy Search
SK Narayanaswami, N Sudarsanam, B Ravindran
Proceedings of the 5th Joint International Conference on Data Science …, 2022
12022
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Articles 1–20