N. Sudarsanam

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Improved Insights on Financial Health through Partially Constrained Hidden Markov Model Clustering on Loan Repayment Data

Balaraman Ravindran, Nandan Sudarsanam, Dibu John Philip, 2018, Data Base.

Ensembles of Adaptive One-Factor-ata-time Experiments : Methods , Evaluation , and Theory by Nandan Sudarsanam

R. Welsch, R. Noyce, N. Sudarsanam, 2008 .

Quantifying the maximum possible improvement in $$2^{k}$$ experiments

N. Sudarsanam, D. Frey, Anusha Kumar, 2022, Research in Engineering Design.

A Decision-Making Framework for Entrepreneurial Venture in Emerging Economies

N. Sudarsanam, S. Kumar, 2022, International Journal of Global Business and Competitiveness.

Regularities in data from factorial experiments

Xiang Li, Daniel D. Frey, Nandan Sudarsanam, 2006, Complex..

Quantifying the maximum possible improvement in 2k experiments Nandan Sudarsanam1 · Anusha Kumar2 · Daniel D. Frey3

N. Sudarsanam, D. Frey, Anusha Kumar, 2022 .

Optimal replicates for designed experiments under the online framework

N. Sudarsanam, D. Frey, Balaji Pitchai Kannu, 2019, Research in Engineering Design.

Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic

N. Sudarsanam, Saish Jaiswal, R. Subburaj, 2022, Humanities and Social Sciences Communications.

Relationship between mobility and road traffic injuries during COVID-19 pandemic—The role of attendant factors

N. Sudarsanam, R. Subburaj, Kandaswamy Paramasivan, 2022, PloS one.

Bacteriological investigations for short-course chemotherapy under the tuberculosis programme in two districts of India.

N. Sudarsanam, C. N. Paramasivan, R. Prabhakar, 1993, Tubercle and Lung Disease.

Ensembles of Adaptive One-Factor at-a-Time experiments : methods, evaluation, and theory

Nandan Sudarsanam, N. Sudarsanam, 2008 .

FEASIBILITY OF UTILISING ADDRESS CARD SYSTEM FOR OBTAINING ACCURATE ADDRESS OF PATIENTS UNDER PROGRAMME CONDITIONS

Chandrasekaran, N. Sudarsanam, G. Shanmugam, 1994 .

An Adaptive One-Factor-at-a-Time Method for Robust Parameter Design: Comparison With Crossed Arrays via Case Studies

Daniel D. Frey, Nandan Sudarsanam, N. Sudarsanam, 2008 .

Using Linear Stochastic Bandits to extend traditional offline Designed Experiments to online settings

Balaraman Ravindran, Nandan Sudarsanam, Balaraman Ravindran, 2018, Comput. Ind. Eng..

Using ensemble techniques to advance adaptive one‐factor‐at‐a‐time experimentation

Daniel D. Frey, Nandan Sudarsanam, N. Sudarsanam, 2011, Qual. Reliab. Eng. Int..

Designing Dynamic Interventions to Improve Adherence in Pediatric Long-Term Treatment – The Role of Perceived Value of the Physician by Primary Caregivers

N. Sudarsanam, A. Manoharan, V. Vijayalakshmi, 2020, Health communication.

A Decision-Making Framework for Entrepreneurial Venture in Emerging Economies

N. Sudarsanam, S. Kumar, 2022, International Journal of Global Business and Competitiveness.

Impact of COVID-19 pandemic on road safety in Tamil Nadu, India

N. Sudarsanam, Kandaswamy Paramasivan, 2021, International journal of injury control and safety promotion.

Rate of change analysis for interestingness measures

Balaraman Ravindran, Abhishek Sharma, Nandan Sudarsanam, 2017, Knowledge and Information Systems.

Crime registration and distress calls during COVID-19: two sides of the coin

N. Sudarsanam, R. Subburaj, Kandaswamy Paramasivan, 2022, Policing and Society.

Optimal replicates for designed experiments under the online framework

Daniel D. Frey, Nandan Sudarsanam, Balaji Pitchai Kannu, 2019, Research in Engineering Design.

Efficient-UCBV: An Almost Optimal Algorithm using Variance Estimates

Balaraman Ravindran, Nandan Sudarsanam, Subhojyoti Mukherjee, 2017, AAAI.

Thresholding Bandits with Augmented UCB

Balaraman Ravindran, Nandan Sudarsanam, Kolar Purushothama Naveen, 2017, IJCAI.

MAPK SIGNALING PATHWAY ANALYSIS ESD . 342 FINAL PROJECT REPORT – MAY 16 , 2006

G. Bounova, N. Sudarsanam, M. Hanowsky, 2006 .

An Active Learning Framework for Efficient Robust Policy Search pdf

Balaraman Ravindran, Nandan Sudarsanam, Sai Kiran Narayanaswami, 2018, COMAD/CODS.

A Partial Parameter HMM Based Clustering on Loan Repayment Data: Insights into Financial Behavior and Intent to Repay

Balaraman Ravindran, Nandan Sudarsanam, Dibu John Philip, 2018, HICSS.

Recent advancements in revenue management of taxi services: a systematic review and research agenda

N. Sudarsanam, R. Marathe, Swaminathan Rammohan, 2023, Management Review Quarterly.

Profitable market mechanism for platform-based aggregator taxi services

N. Sudarsanam, R. Marathe, Swaminathan Rammohan, 2022, Transportation Research Interdisciplinary Perspectives.

Ensembles of Adaptive One-Factor at-a-Time experiments : methods, evaluation, and theory

N. Sudarsanam, 2008 .

Conducting Non-adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size

Daniel D. Frey, Nandan Sudarsanam, Ramya Chandran, 2019, Journal of Mechanical Design.