My papers on Google Scholar and arXiv.

Working papers and preprints

  1. Qiu, Y., Wang, J., Lei, J., and Roeder, K. (2020)
    Identification of cell-type-specific marker genes from co-expression patterns in tissue samples
  2. Hu, X. and Lei, J. (2020)
    A Distribution-Free Test of Covariate Shift Using Conformal Prediction
  3. Lei, J. and Lin, K. Z., (2021)
    Bias-adjusted spectral clustering in multi-layer stochastic block models
  4. Qiu, Y., Lei, J., and Roeder, K. (2019)
    Gradient-based sparse principal component analysis with extensions to online learning
  5. Wang, Y., Lei, J., and Fienberg, S. (2016)
    A minimax theory for adaptive data analysis

Peer-Reviewed Articles: Theory and Methodology

  1. Lin, K. Z., Lei, J., and Roeder, K. (2020)
    Exponential-family embedding with application to cell developmental trajectories for single-cell RNA-seq data
    Journal of the American Statistical Association, to appear.
  2. Lei, J. (2021)
    Network representation using graph root distributions
    Annals of Statistics, 49(2), 745-768.
  3. Lei, J. (2020)
    Cross-validation with confidence [code]
    Journal of the American Statistical Association, 115(532), 1978-1997.
  4. Lei, J. and Kadane, J. B. (2020)
    On the probability that two random integers are coprime
    Statistical Science, 35(2) 272-279.
  5. Lei, J. and Lin, K. (2020)
    Discussion of ‘Network cross-validation by edge sampling’ [code]
    Biometrika, 107(2), 285-287.
  6. Lei, J. (2020)
    Convergence and concentration of empirical measures under Wasserstein distance in unbounded functional spaces
    Bernoulli, 26(1), 767-798.
  7. Lei, J., Chen, K., and Lynch, B. (2020)
    Consistent community detection in multi-layer network data [code]
    Biometrika, 107(1), 61-73.
  8. Kim, I., Lee, A. B., and Lei, J. (2019)
    Global and local two-sample tests via regression
    Electronic Journal of Statistics, 13(2), 5253-5305.
  9. Lei, J. (2019)
    Fast exact conformalization of Lasso using piecewise linear homotopy [code]
    Biometrika, 106(4), 749–764.
  10. Zhu, L., Lei, J., Klei, L., Devlin, B., and Roeder, K. (2019)
    Semi-soft clustering of single cell data
    Proceedings of the National Academy of Sciences, 116(2), 466-471.
  11. Vu, V. Q. and Lei, J. (2019)
    Squared-norm empirical processes
    Statistics & Probability Letters, 150, 108-113.
  12. Sadinle, M., Lei, J., and Wasserman, L. (2019)
    Least ambiguous set-valued classifiers with bounded error levels
    Journal of the American Statistical Association, 114(525), 223-234.
  13. Zhu, L., Lei, J., and Roeder, K. (2018)
    A unified statistical framework for single cell and bulk RNA sequencing data
    Annals of Applied Statistics, 12(1), 609-632.
  14. Lei, J., G'Sell, M., Rinaldo, A., Tibshirani, R. J. and Wasserman, L. (2018)
    Distribution-free predictive inference for regression [R Package]
    Journal of the American Statistical Association, 113(523), 1094-1111.
  15. Lei, J., Charest, A.-S., Slavkovic, A., Smith, A., and Fienberg, S. (2018)
    Differentially private model selection with penalized and constrained likelihood
    Journal of the Royal Statistical Society, Series A, 181, 609-633.
  16. Chen, K. and Lei, J. (2018)
    Network cross-validation for determining the number of communities in network data [code]
    Journal of the American Statistical Association, 113(521), 241-251.
  17. Lei, J. and Zhu, L. (2017)
    Generic sample splitting for refined community recovery in degree corrected stochastic block models [code]
    Statistica Sinica, 27, 1639-1659.
  18. Zhu, L., Lei, J., Devlin, B., and Roeder, K. (2017)
    Testing high dimensional differential matrices, with application to detecting schizophrenia risk genes
    Annals of Applied Statistics, 11(3), 1810−1831.
  19. Wang, Y., Lei, J., and Fienberg, S. (2016)
    On-average KL-privacy and its equivalence to generalization for max-entropy mechanisms
    Privacy in Statistical Databases. PSD'2016, Dubrovnik.
  20. Wang, Y., Lei, J., and Fienberg, S. (2016)
    Learning with differential privacy: stability, learnability and the sufficiency and necessity of ERM principle
    Journal of Machine Learning Research, 17(183), 1−40.
  21. Lei, J. (2016)
    A goodness-of-fit test for stochastic block models [code]
    Annals of Statistics, 44(1), 401-424.
  22. Chen, K. and Lei, J. (2015)
    Localized functional principal component analysis [code]
    Journal of the American Statistical Association, 110, 1266-1275.
  23. Liu, L., Lei, J., and Roeder, K. (2015)
    Network assisted analysis to reveal the genetic basis of autism
    Annals of Applied Statistics, 9(3), 1571-1600.
  24. Lei, J. and Vu, V. Q. (2015)
    Sparsistency and agnostic inference in sparse PCA
    Annals of Statistics, 43(1), 299-322.
  25. Lei, J. and Rinaldo, A. (2015)
    Consistency of spectral clustering in stochastic block models
    Annals of Statistics, 43(1), 215-237.
  26. Lei, J., Rinaldo, A., and Wasserman, L. (2015)
    A conformal prediction approach to explore functional data
    Annals of Mathematics and Artificial Intelligence, 74(1-2), 29-43.
  27. Lei, J. (2014)
    Classification with confidence [code]
    Biometrika, 101(4), 755-769.
  28. Lei, J. (2014)
    Adaptive global testing for functional linear models [code]
    Journal of the American Statistical Association, 109, 624-634.
  29. Lei, J. and Wasserman, L. (2014)
    Distribution free prediction bands for nonparametric regression [code]
    Journal of the Royal Statistical Society, Series B, 76, 71-96.
  30. Vu, V. Q. and Lei, J. (2013)
    Minimax sparse principal subspace estimation in high dimensions
    Annals of Statistics, 41, 2905-2947.
  31. Vu, V. Q., Cho, J., Lei, J., and Rohe, K. (2013)
    Fantope projection and selection: A near-optimal convex relaxation of sparse PCA [R package]
    Annual Conference on Neural Information Proceeding Systems, 26 (NIPS'13).
  32. Lei, J., Robins, J., and Wasserman, L. (2013)
    Distribution free prediction sets [code]
    Journal of the American Statistical Association, 108, 278-287.
  33. Lei, J. and Bickel, P. (2013)
    On convergence of recursive Monte Carlo filters in non-compact state spaces
    Statistica Sinica, 23, 429-450.
  34. Vu, V. Q. and Lei, J. (2012)
    Minimax rates of estimation for sparse PCA in high dimensions
    Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS'12, Best Paper Award).
  35. Lei, J. and Bickel, P. (2011)
    A moment-matching approach to nonlinear non-Gaussian ensemble filtering
    Monthly Weather Review, 139, 3964-3973.
  36. Lei, J. (2011)
    Differentially private M-estimators [supplementary] [code]
    Annual Conference on Neural Information Proceeding Systems, 24 (NIPS'11).
  37. Lei, J., Bickel, P., and Snyder, C. (2010)
    Comparison of ensemble Kalman filters under non-Gaussianity
    Monthly Weather Review, 138, 1293-1306.
  38. Dwork, C. and Lei, J. (2009)
    Differential privacy and robust statistics [Full Version]
    Proceedings of the 41st Annual ACM Symposium on Theory of Computing (STOC'09).

Peer-Reviewed Articles: Application

  1. Cotney, J. et al. (2015)
    The autism-associated chromatin modifier ​CHD8 regulates other autism risk genes during human neurodevelopment
    Nature Communications, 6:6404.
  2. De Rubeis, S. et al. (2014)
    Synaptic, transcriptional and chromatin genes disrupted in autism
    Nature, 515, 209-215
  3. Liu, L., Lei, J., et al. (2014)
    DAWN: A framework to identify autism genes and subnetworks using gene expression and genetics
    Molecular Autism, 5:22.
  4. Willsey, J. et al. (2013)
    Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism
    Cell, 155, 997-1007.

Notes

  1. Bernstein's inequality using Orlicz psi_1 norm