| A PENALIZED EMPIRICAL LIKELIHOOD METHOD IN HIGH DIMENSIONS SN Lahiri, S Mukhopadhyay Annals of Statistics, 2012 | 56 | 2012 |
| Large-scale mode identification and data-driven sciences S Mukhopadhyay | 28 | 2017 |
| A nonparametric approach to high-dimensional k-sample comparison problems S Mukhopadhyay, K Wang Biometrika 107 (3), 555-572, 2020 | 19 | 2020 |
| LP approach to statistical modeling S Mukhopadhyay, E Parzen arXiv preprint arXiv:1405.2601, 2014 | 19 | 2014 |
| Nonparametric distributed learning architecture for big data: Algorithm and applications S Bruce, Z Li, HC Yang, S Mukhopadhyay IEEE Transactions on Big Data 5 (2), 166-179, 2018 | 16 | 2018 |
| Runaway electron studies in the startup phase of very low edge safety factor (qa)(VLQ) discharges in the SINP tokamak ANS Iyengar, R Pal, S Lahiri, S Mukhopadhyay Nuclear fusion 38 (8), 1177, 1998 | 13 | 1998 |
| Modeling, dependence, classification, united statistical science, many cultures E Parzen, S Mukhopadhyay arXiv preprint arXiv:1204.4699, 2012 | 12 | 2012 |
| Generalized empirical Bayes modeling via frequentist goodness of fit S Mukhopadhyay, D Fletcher Scientific reports 8 (1), 9983, 2018 | 11 | 2018 |
| LPiTrack: Eye movement pattern recognition algorithm and application to biometric identification S Mukhopadhyay, S Nandi Machine Learning 107, 313-331, 2018 | 11 | 2018 |
| Large‐scale signal detection: A unified perspective S Mukhopadhyay Biometrics 72 (2), 325-334, 2016 | 11 | 2016 |
| Nonparametric universal copula modeling S Mukhopadhyay, E Parzen Applied Stochastic Models in Business and Industry 36 (1), 77-94, 2020 | 10 | 2020 |
| United statistical algorithms, LP comoment, copula density, nonparametric modeling E Parzen, S Mukhopadhyay 59th ISI World Statistics Congress (WSC), Hong Kong, 4719-4724, 2013 | 10 | 2013 |
| Breiman's" two cultures" revisited and reconciled K Wang arXiv preprint arXiv:2005.13596, 2020 | 8 | 2020 |
| United Statistical Algorithm, Small and Big Data: Future OF Statistician E Parzen, S Mukhopadhyay arXiv preprint arXiv:1308.0641, 2013 | 8 | 2013 |
| InfoGram and admissible machine learning S Mukhopadhyay Machine Learning 111 (1), 205-242, 2022 | 6 | 2022 |
| Nonlinear time series modeling: A unified perspective, algorithm and application S Mukhopadhyay, E Parzen Journal of Risk and Financial Management 11 (3), 37, 2018 | 6 | 2018 |
| Nonlinear time series modeling by LPTime, nonparametric empirical learning S Mukhopadhyay, E Parzen arXiv preprint arXiv:1308.0642, 2013 | 6 | 2013 |
| Bayesian multiscale smoothing in supervised and semi-supervised kernel discriminant analysis S Mukhopadhyay, AK Ghosh Computational Statistics & Data Analysis 55 (7), 2344-2353, 2011 | 6 | 2011 |
| LP mixed data science: Outline of theory E Parzen, S Mukhopadhyay arXiv preprint arXiv:1311.0562, 2013 | 5 | 2013 |
| From data to constraints S Mukhopadhyay, E Parzen, SN Lahiri AIP Conference Proceedings 31st 1443 (1), 32-39, 2012 | 4 | 2012 |
