My research is partially supported by National Science Foundation and Simons Foundation.
My google scholar page.
Manuscripts
Wang, Z., Fang, Y., Liu, Z., Hao, N., Zhang, H.H., Sun, X., Que, J., and Ding, H. (2023)
Adapting Nanopore Sequencing Basecalling Models for Modification Detection via Incremental Learning and Anomaly Detection.
[bioRxiv]
Journal Papers
Zhao, Y., Hao, N., and Zhu, J. (2024)
Variational Estimators of the Degreecorrected Latent Block Model for Bipartite Networks.
Journal of Machine Learning Research, to appear. [arXiv]
Lu, Z., Hao, N. and Zhang, H.H. (2024)
Simultaneous Changepoint Detection and Curve Estimation.
Statistics and Its Interface, to appear. R package SCHACE
Hao, N., Niu, Y.S. and Xiao, H. (2023)
Equivariant Variance Estimation for Multiple Changepoint Model.
Electronic Journal of Statistics, 17, 38113853. [PDF] [arXiv]
Wu, R. and Hao, N. (2022)
Quadratic Discriminant Analysis by Projection.
Journal of Multivariate Analysis, 190. [PDF] [arXiv]; R package QDAP
Hao, N., Niu, Y.S., Xiao, F. and Zhang, H. (2021)
A Super Scalable Algorithm for Short Segment Detection.
Statistics in Biosciences, 13, 1833. [PDF]
[arXiv]; R package SSSS
Shin, S.J., Wu, Y. and Hao, N. (2020)
A Backward Procedure for Changepoint Detection with Application to Copy Number Variation Detection.
The Canadian Journal of Statistics, 48, 366385. [PDF]
[arXiv]; R package bwd
Xiao, F., Luo, X., Hao, N., Niu, Y.S., Xiao, X., Cai, G., Amos, C.I., and Zhang, H. (2019)
An Accurate and Powerful Method for Copy Number Variation Detection.
Bioinformatics, 35, 28912898. [PDF];
R package modSaRa2
Hao, N., Feng, Y. and Zhang, H.H. (2018)
Model Selection for High Dimensional Quadratic Regressions via Regularization.
Journal of the American Statistical Association, 113, 615625. [PDF]
[arXiv]; R package RAMP
Niu, Y.S., Hao, N. and Zhang, H.H. (2018)
Interaction Screening by Partial Correlation.
Statistics and Its Interface, 11, 317325. [PDF]
Niu, Y.S., Hao, N. and Dong, B. (2018)
A New ReducedRank Linear Discriminant Analysis Method and Its Applications.
Statistica Sinica, 28, 189202. [PDF]
[arXiv]; R package SPCALDA
Hao, N. and Zhang, H.H. (2017)
A Note on High Dimensional Linear Regression with Interactions.
The American Statistician, 71, 291297. [PDF]
[arXiv]
Hao, N. and Zhang, H.H. (2017)
Oracle Pvalues and Variable Screening.
Electronic Journal of Statistics, 11, 32513271. [PDF]; R codes
Xiao, F., Niu, Y.S., Hao, N., Xu, Y., Jin, Z. and Zhang, H. (2017)
modSaRa: a computationally efficient R package for CNV identification
Bioinformatics, btx212. [PDF];
R package modSaRa
Niu, Y.S., Hao, N. and Zhang, H. (2016).
Multiple ChangePoint Detection, a Selective Overview.
Statistical Science, 31, 611623. [PDF]
[arXiv]
Hao, N., Dong, B. and Fan, J. (2015)
Sparsifying the Fisher Linear Discriminant by Rotation.
Journal of the Royal Statistical Society: Series B, 77, 827851. [PDF] [arXiv];
Matlab codes
Hao, N. and Zhang, H.H. (2014).
Interaction Screening for UltraHigh Dimensional Data.
Journal of the American Statistical Association, 109, 12851301. [PDF]; Matlab codes
Hao, N., Niu, Y.S. and Zhang, H. (2013).
Multiple ChangePoint Detection via a Screening and Ranking Algorithm.
Statistica Sinica, 23, 15531572. [PDF]; R package SaRa
Fan, J., Guo, S. and Hao, N. (2012).
Variance Estimation Using Refitted CrossValidation in Ultrahigh Dimensional Regression.
Journal of the Royal Statistical Society: Series B, 74, 3765. [PDF]
Conference Papers
Niu, Y.S., Hao, N. and An, L. (2011).
Detection of Rare Functional Variants Using Group ISIS.
BMC Proceedings, 5(Suppl 9):S108. [PDF]
Miscellaneous
Ph.D. dissertation: Dbar Spark Theory and Deligne Cohomology
Key words: CheegerSimons differential characters, Chern classes, HarveryLawson spark characters, hypercohomology, Massey product, Nadelâ€™s conjecture, secondary geometric invariants.
The main results of my dissertation were uploaded in arXiv:
