Publications

  1. E. Fang, Y. Mei, Y. Shi, Q. Xu, and T. Zhao. Pivotal estimation of linear discrminant analysis in high dimensions. Journal of Machine Learning Research (JMLR), 24 (302), pages 1-45, 2023.
  2. I. Erazo, D. Goldsman, and Y. Mei. Cost-efficient fixed-width confidence intervals for the difference of two Bernoulli Proportions. Journal of Simulation, August 2023 (Accepted) [Arxiv version].
  3. Y. Shi, A. Deshmukh, Y. Mei, and V. V. Veeravalli. Robust high-dimensional linear discriminant analysis under training data contamination. 2023 IEEE International Symposium on Information Theory (ISIT), pages 2099-2104, 2023.
  4. A. Kumar, M. Y. Hu, Y. Mei, and Y. Fan. CSSQ: A ChIP-seq Signal Quantifier Pipeline. Frontiers in Cell and Developmental Biology, Section Epigenomics and Epigenetics. Vol. 11, May 2023.
  5. Q. Xu and Y. Mei. Asymptotic optimality theory for active quickest detection with unknown post-change parameters. Sequential Analysis, Vol. 42, no. 2, pages 150-181, 2023.
  6. H. Tian, R. Z. Cohen, C. Zhang, and Y. Mei. Active learning-based multistage sequential decision-making model with application on common bile duct stone evaluation. Journal of Applied Statistics, January 2023 (Accepted).
  7. W. Zhang and Y. Mei. Bandit change-point detection for real-time monitoring high-dimensional data under sampling control. Technometrics, 65(1): 33-43, 2023.
  8. Y. Zhao, X. Huo, and Y. Mei. Identification of Partial-Differential-Equations-Based Models from Noisy Data via Splines. Statistica Sinica, November 2022 (Accepted).
  9. J. Hu, Y. Mei, S. Holte, and H. Yan. Adaptive resource allocation CUSUM for Binomial count data monitoring with application to COVID-19 hotspot detection. Journal of Applied Statistic, August 2022 (Accepted).
  10. X. Zhao, J. Hu, Y. Mei, and H. Yan. Adaptive partially-observed sequential change detection and isolation. Technometrics, 64(4): 502-512, 2022.
  11. Y. Zhao. X. Huo, and Y. Mei. Hot-spot detection in count data by Poisson assisted smooth sparse tensor decomposition. Journal of Applied Statistics, July 2022 (Accepted). Here is the arxiv version.
  12. Y. He, N. Suh, X. Huo, S. H. Kang, and Y. Mei. Asymptotic theory of $\ell_1$-regularized PDE identification from a single noisy trajectory. SIAM/ASA Journal on Uncertainty Quantification, 10(3): 1012-1036, 2022.
  13. R. Zhang, Y. Mei, J. Shi, and H. Xu. Robustness and tractability for non-convex M-estimators, Statistica Sinica, Vol. 32, pages 1295-1316, 2022.
  14. Y. Zhao, H. Yan, S. E. Holte, and Y. Mei. Rapid detection of hot-spot via tensor decomposition with application to crime rate data, Journal of Applied Statistics, 49(7): 1636-1662, 2022.
  15. H. Tian, A. Wang, J. Chen, X. Jiang, J. Shi, C. Zhang, Y. Mei, and B. Wang, “Treatment effect modeling for FTIR signals subject to multiple sources of uncertainties.” IEEE Transactions on Automation Science and Engineering, vol. 19, no. 2, page 895-906, 2022.
  16. R. Zhang, Y. Mei, and J. Shi. Robust change detection for large-scale data streams, Sequential Analysis, vol. 41, issue 1, page 1-19, 2022. (The conference poster version won one of the best student poster award in the 5th workshop on Biostatistics and Bioinformatics, Georgia State University, Atlanta, GA)
  17. S. Philips, Y. Shi, C. M. Coopersmith, O. B. Samuel, C. P. Farias, Y. Mei, O. Sadan, and F. Akbik. Surge capacity in the COVID-19 Era: a natural experiment of neurocritical care in general critical care. Neurocrit Care. July 13: 1-6, 2022. PMID: 3583173; PMCID: PMC9281288.
  18. O. Canbek, Q. Xu, Y. Mei, N. R. Washburn, and K. E. Kurtis. Predicting the rheology of limestone calcined clay cements (LC^3): Linking composition and hydration kinetics to yield stress through machine learning. Cement and Concrete Research, vol 160, 106925, 2022.
  19. F. Akbik, H.D. Konan, K.P Williams, L. M. Ermias, Y. Shi, O. Takieddin, J.A. Grossberg, B.M. Howard, F. Tong, C. M. Cawley, Y. Mei, O. B. Samuel, and O. Sadan. Cannabis use is not associated with aneurysmal subarachnoid hemorrhage complications or outcomes. Stroke, 53(8):e375-376. Aug 2022.
  20. Y. Luo, X. Huo, and Y. Mei. The directional bias helps stochastic gradient descent to generalize in kernel regression models. 2022 IEEE International Symposium on Information Theory (ISIT). pp. 678-683, 2022.
  21. Y. Luo, X. Huo, and Y. Mei. Implicit regularization properties of variance reduced stochastic mirror descent. 2022 IEEE International Symposium on Information Theory (ISIT). pp. 696-701, 2022.
  22. Q. Xu and Y. Mei. Active quickest detection when monitoring multi-streams with two affected streams. 2022 IEEE International Symposium on Information Theory (ISIT), pp. 1915-1920, 2022.
  23. W. Zhang, Y. Mei, and R. Cummings. Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size. [arXiv version]. Proceedings of The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), PMLR 151:11356-11373, 2022. 
  24. W. Zhang, S. Krehbiel, R. Tuo, Y. Mei, and R. Cummings. Single and Multiple Change-Point Detection with Differential Privacy, Journal of Machine Learning Research (JMLR), 22(29): 1-36, 2021.
  25. Q. Xu, Y. Mei, and G.V. Moustakides. Optimum multi-stream sequential change-point detection with sampling control. IEEE Transaction on Information Theory, Vol. 67, no. 11, pages 7627-7636, 2021.
  26. C. Feng, P. Griffin, S. Kethireddy, and Y. Mei. A boosting-inspired personalized thresholding method for sepsis screening, Journal of Applied Statistics, 48(1): 154-175, 2021. (The conference poster version won the best student poster award (1st place) in the 2018 Georgia Statistics Day in the University of Georgia, Athens on October 26, 2018).
  27. M. Nabhan, Y. Mei, and J. Shi. Correlation-based Dynamic Sampling for online high-dimensional process monitoring, Journal of Quality Technology, 53(3): 289-308, 2021.
  28. W. Li, C. Zhang, F. Tsung, and Y. Mei. Nonparametric monitoring of multivariate data via KNN learning, International Journal of Production Research, 59 (20): 6311-6326. 2021.
  29. R. Z. Cohen, H. Tian, C. G. Sauer, F. F. Willingham, M. T. Santore, Y. Mei, and A. J. Freeman. Creation of a pediatric Choledocholithiasis Prediction Model, Journal of Pediatric Gastroenterology & Nutrition, 73(5):636-641, 2021.
  30. A. Archer, L.F. Sestito, M. P. Manspeaker, M. J. O’Melia, N.A. Rohner, A. Schudel, Y. Mei, and S. N. Thomas. Quantitation of lymphatic transport mechanism and barrier influences on lymph node-resident leukocyte access to lymph-borne macromolecules and drug delivery systems, Drug Delivery and Translational Research, vol. 11, issue 6, pages 2328-2343, 2021.
  31. J. L. Woodall, J. A. Sak, K. R. Cowdrick, B. M.B. Munoz, J. H. McElrath, G. R. Trimpe, Y. Mei, R. L. Myhre, J. K. Raine, C. R. Hutchinson, “Repetitive low-level blast exposure and neurocognitive effects in army ranger mortarmen,” Military Medicine, usab394, pages 1-9, 2021.
  32. O. Samuels, O. Sadan, C. Feng, K. Martin, K. Medani, Y. Mei, and D. L. Barrow. Aneurysmal subarachnoid hemorrhage: trends, outcomes, and predictions from a 15-year perspective of a single neurocritical care unit. Neurosurgery. vol. 88, issue 3, pages 574-583, 2021.
  33. O. Sadan, H. Waddel, R. Moore, C. Feng, Y. Mei, D. Pearce, J. Kraft, C. Pimentel, S. Matthew, F. Akbik, P. Ameli, A. Taylor, L .Danyluk, K. S. Martin, K. Garner, J. Kolenda, A. Pujari, W. Asbury, B. NR Jaja, R L. Macdonald, C. M. Cawley, D. L. Barrow, O. Samuels. Does intrathecal nicardipine for cerebral vasospasm following subarachnoid hemorrhage correlate with reduced delayed cerebral ischemia? A retrospective propensity score-based analysis. Journal of Neurosurgery, vol. 136, issue 1, pages 115-124. 2021.
  34. Q. Xu and Y. Mei. Multi-Stream Quickest Detection with Unknown Post-Change Parameters Under Sampling Control, 2021 IEEE International Symposium on Information Theory (ISIT), pages 112-117, 2021.
  35. K. Liu and Y. Mei. Improved performance properties of the CISPRT algorithm for distributed sequential detection, Signal Processing,  172 (107573): 1-10, 2020.
  36. C. Feng, Y. Mei, and B. Vidakovic. Wavelet-based robust estimation of hurst exponent with application in visual impairment classification, Journal of Data Science, 18(4): 581-605, 2020.
  37. O. Sadan, C. Feng, B. Vidakovic, Y. Mei, K. Martin, O. Samuel, and CL Hall. Glucose variability as measured by inter-measurement percentage change is predictive of in-patient mortality in aneurysmal subarachnoid hemorrhage. Neurocritical Care, vol. 33, issue 2, pages 458-467, 2020.
  38. Q. Xu, Y. Mei, and G. V. Moustakides. Second-order asymptotically optimal change-point detection algorithm with sampling control, 2020 IEEE International Symposium on Information Theory (ISIT), 2020, pp. 1136-1140, doi: 10.1109/ISIT44484.2020.9174114.
  39. Y. Zhao, H. Yan, S. E. Holte, R. P. Kerani, and Y. Mei. Rapid detection of hot-spot by tensor decomposition with application to weekly gonorrhea data, page 289-310, Proceedings of 13th Internal Workshop on Intelligent Statistical Quality Control 2019, IWSQC 2019 – Hong Kong, Hong Kong, August 12-14, 2019. This conference paper is also accepted as a book chapter in the book entitled “Frontiers in Statistical Quality Control 13” in Aug 2020.
  40. T. Yaacoub, D. Goldsman, Y. Mei, and G. V. Moustakides. Tandem-width sequential confidence intervals for a Bernoulli proportion, Sequential Analysis, vol. 38, issue 2, pages 163-183, 2019.
  41. T. Yaacoub, G. V. Moustakides, and Y. Mei. Optimal stopping for interval estimation in Bernoulli trials, IEEE Transactions on Information Theory, vol. 65, page 3022-3033, 2019.
    (The conference poster version won one of the best student poster awards in the 2017 Georgia Statistics Day in Emory University on October 9, 2017).
  42. K. Liu, R. Zhang and Y. Mei. Scalable SUM-shrinkage schemes for distributed monitoring large-scale data streams, Statistica Sinica, vol. 29, page 1-22, 2019.
  43. N. Suh, R. Zhang, and Y. Mei. Adaptive online monitoring of the Ising model. 2019 57th Annual Allerton Conference on Communication, Control, and Computing, pages 426-431, 2019.
  44. R. Zhang and Y. Mei. Asymptotic statistical properties of communication-efficient quickest detection schemes in sensor networks, Sequential Analysis, vol. 37, issue 3, page 375-396, 2018.
  45. R. Cummings, S. Krehbiel, Y. Mei, R. Tuo and W. Zhang. Differentially private change-point detection, Arxiv, 2018. The conference paper version is accepted by the thirty-second Conference on Neural Information Processing Systems (NIPS 2018).
  46. Yuan Wang, Y. Mei and K. Paynabar. Thresholded multivariate principal component analysis for phase I multichannel profile monitoring, Technometrics, vol. 60, issue 3, page 360-372, 2018.
  47. C. Feng, Y. Mei and B. Vidakovic. Mammogram diagnostics using robust wavelet-based estimator of Hurst exponent, In Y. Zhao and D. G. Chen (ed.) New Frontiers in Biostatistics and Bioinformatics, Cham, Switzerland: Springer, pages 109-140, 2018.
    (The conference poster version won one of the best student poster award in the 6th workshop on Biostatistics and Bioinformatics, Georgia State University, Atlanta, GA)
  48. R. Zhang, Y. Mei and J. Shi. Wavelet-based profile monitoring using order-thresholding recursive CUSUM schemes, In Y. Zhao and D. G. Chen (ed.) New Frontiers in Biostatistics and Bioinformatics, Cham, Switzerland: Springer, pages 141-159, 2018.
  49. S.E. Holte and Y. Mei. Precision in the specification of ordinary differential equations and parameter estimation in modelling biological processes, In C. Chan, M. G. Hudgens, and S.-C. Chow (ed.) Quantitative Methods for HIV/AIDS Research, Boca Raton, FL: CRC press, page 257-282, 2017.
  50. R. Zhang, J. Wang, and Y. Mei. Search for evergreens in science: a functional data analysis, Journal of Informetrics, vol. 11, issue 3, page 629-644, 2017.
  51. G. Moustakides, T. Yaacoub, and Y. Mei. Sequential estimation based on conditional cost, Proceedings of 2017 IEEE International Symposium on Information Theory, Aachen, Germany, page 436-440, June 25-30, 2017.
  52. S.E. Holte, E. Lee and Y. Mei. Symmetric directional false discovery rate control, Statistical Methodology, vol. 33, page 71-82, 2016.
  53. K. Liu and Y. Mei. Discussion on “Sequential detection/isolation of abrupt changes’ by Igor Nikiforov, Sequential Analysis, vol. 35, page 316-319, 2016.
  54. Y. Li and Y. Mei. Effect of bivariate data’s correlation on sequential tests of circular error probability. Journal of Statistical Planning and Inference, vol. 171, page 99-114, 2016.
  55. Yuan Wang and Y. Mei. Large-Scale multi-stream quickest change detection via shrinkage post-change estimation. IEEE Transactions on Information Theory, vol. 61, page 6926-6938, 2015.
  56. C.D. Fuh and Y. Mei. Quickest change detection and Kullback-Leibler divergence for two-state hidden Markov models. IEEE Transactions on Signal Processing, vol. 63, No. 18, page 4866-4878, 2015.
  57. K. Liu, Y. Mei and J. Shi. An adaptive sampling strategy for online high-dimensional process monitoring. Technometrics, vol. 57, No. 3, page 305-319, 2015.
  58. J. Wang, Y. Mei and D. Hicks. Comments on “Quantifying long-term scientific impact”. Science, vol. 345 no. 6193, page 149, 2014.
  59. Y. Wang and Y. Mei. Quantization effect on the log-likelihood ratio and its application to decentralized sequential detection. IEEE Transactions on Signal Processing, vol. 61, issue 6, page 1536-1543, 2013.
  60. Y. Wang and Y. Mei. A multistage procedure for decentralized sequential multi-hypothesis testing problems. Sequential Analysis, vol. 31, pp. 505-527, 2012.
  61. Y. Mei. Quickest detection in censoring sensor networks, Proceedings of 2011 IEEE International Symposium on Information Theory, St. Petersburg, Russia, page 2148-2152, July 31- Aug 5, 2011.
  62. Y. Wang and Y. Mei. Asymptotic optimality theories for decentralized multi-hypothesis sequential detection. IEEE Transactions on Information Theory, vol. 57, issue 10, page 7068-7083, 2011.
  63. Y. Mei, S. W. Han and K. Tsui. Early detection of a change in Poisson rate after accounting for population size effects. Statistica Sinica, vol. 21, page 597-624, 2011.
  64. Y. Mei. Efficient scalable schemes for monitoring a large number of data streams. Biometrika, vol. 97, page 419-433, 2010.
  65. Y. Mei, “Is average run length to false alarm always an informative criterion?” (with discussions), Sequential Analysis, vol. 27, page 354-419, 2008.
  66. Y. Mei, “Asymptotic optimality theory for decentralized sequential hypothesis testing in sensor networks,” IEEE Transactions on Information Theory, vol. 54, issue 5, page 2072-2089, 2008.
  67. Y. Mei, L. Wang, and S. E. Holte. “A comparison of methods for determining HIV viral set point.” Statistics in Medicine, vol. 27, issue 1, page 121-139, 2008.
  68. Y. Mei, Suboptimal properties of Page’s CUSUM and Shiryayev-Roberts procedures in change-point problems with dependent observations. Statistica Sinica, vol. 16, page 883-897, 2006.
  69. Y. Mei, Comments on “A note on optimal detection of a change in distribution” by Benjamin Yakir The Annals of Statistics, vol. 34, no. 3, page 1570-1576, 2006.
  70. Y. Mei, Sequential change-point detection when unknown parameters are present in the pre-change distribution. The Annals of Statistics, vol. 34, no. 1, page 92-122, 2006.
  71. Y. Mei, Information bounds and quickest change detection in decentralized decision systems. IEEE Transactions on Information Theory, vol. 51, issue 7, page 2669-2681, 2005.
  72. Y. Mei, Asymptotically optimal methods for sequential change-point detection. Ph.D. thesis, 2003.