Xingdong Feng
Professor
School of Statistics and Data Science
Shanghai University of Finance and Economics

Research Interests


Distributed Computation in Statistics, Quantile Regression, Statistical Learning, Robust Estimation

Publications


Methodology (Journal)


Ma, H.#, Sang, P., Feng, X., and Liu, X.* (2025+). Robust mixed functional classifier with adaptive large margin loss. Journal of Multivariate Analysis to appear.
Bi, J.#, Feng, X., and Liu, J.* (2025+). Conditional dependence learning with high-dimensional conditioning variables. SCIENCE CHINA Mathematics to appear.
Cheng, C.#, Ma, H.#, Zhong, Y., Uhlemann, A.-C., Feng, X., and Hu, J.* (2025+). Biomarker detection for disease classification in longitudinal microbiome data. The Annals of Applied Statistics to appear.
Su, H.#, Wei, J.#, Li, T., You, J., and Feng, X.* (2025). Influence on Stock Market Yield from Perspective of Industry Heterogeneity. China Journal of Econometrics 5(2), 333-361.
Feng, X., Gao, Y.#, Huang, J., Jiao, Y., and Liu, X.* (2025). Relative entropy gradient sampler for unnormalized distributions. Journal of Computational and Graphical Statistics 34(1), 211-221.
Feng, X., He, X.*, Jiao, Y., Kang, L.*, and Wang, C.# (2024). Deep nonparametric quantile regression under covariate shift. Journal of Machine Learning Research 25(385), 1-50.
Ge, Y.#, Li, T., Feng, X., Wu, M.*, and Liu, H.* (2024). Structured feature ranking for genomic marker identification accommodating multiple types of networks. Biometrics ujae158.
Wang, C.#, Li, T., Zhang, X.#, Feng, X., and He, X.* (2024). Communication-efficient nonparametric quantile regression via random features. Journal of Computational and Graphical Statistics 33, 1175-1184.
Feng, X.*, Li, W.#, and Zhu, Q. (2024). Estimation and bootstrapping under spatiotemporal models with unobserved heterogeneity. Journal of Econometrics 238, 105559.
Feng, X., Jiao, Y., Kang, L.*, Zhang, B. and Zhou, F.* (2023). Over-parameterized deep nonparametric regression for dependent data with its applications to reinforcement learning. Journal of Machine Learning Research 24(383), 1-40.
He, X., Ge, Y.#, and Feng, X.* (2023). Structure learning via unstructured kernel-based M-estimation. Electronic Journal of Statistics 17, 2386-2415.
Feng, X., Li, W.#, and Zhu, Q.* (2023). Spatial-temporal model with heterogeneous random effects. Statistica Sinica 33, 2613-2641.
Yu, A.#, Zhong, Y., Feng, X.*, and Wei, Y. (2023). Quantile regression for nonignorable missing data with its application of analyzing electronic medical records. Biometrics 79, 2036-2049.
Liu, Y.#, Feng, X.*(2023). Clustering ambulatory missing data with applications to hypertension diagnostics (in Chinese). Journal of Applied Statistics and Management 42, 218-228.
Feng, X.*, Liu, Q.#, and Wang, C.# (2023). A lack-of-fit test for quantile regression process models. Statistics and Probability Letters 192, 109680.
Li, X.#, Feng, X., and Liu, X.* (2022). Heritability estimation for a linear combination of phenotypes via ridge regression. Bioinformatics 38, 4687-4696.
Cheng, C.#, Feng, X., Li, X., and Wu, M.* (2022). Robust analysis of cancer heterogeneity for high-dimensional data. Statistics in Medicine 41, 5448-5462.
Zhang, L., Zhu, Z.#, Feng, X., and He, Y.* (2022). Shrinkage quantile regression estimation for panel data models with multiple structural breaks. Canadian Journal of Statistics 50, 820-859.
Liu, Q.#, Feng, X.*(2022). Specification test of polynomials under partially linear additive quantile regression(in Chinese). Journal of Applied Statistics and Management 41, 294-308.
Zhang, S.# and Feng, X.* (2022). Distributed identification of heterogeneous treatment effects. Computational Statistics 37, 57-89. Online Link 
Cheng, C.#, Feng, X.*, Huang, J., Jiao, Y., and Zhang, S.# (2022). ℓ0 -regularized high-dimensional accelerated failure time model. Computational Statistics and Data Analysis 170, 107430. Online Link 
Cheng, C.#, Feng, X., Huang, J. and Liu, X.* (2022). Regularized projection score estimation of treatment effects in high-dimensional quantile regression. Statistica Sinica 32, 23-41.
Dong, C.#, Ma, S., Zhu, L., Feng, X.*(2021). Estimation and inference for non-crossing multiple-index quantile regression(in Chinese). SCIENTIA SINICA Mathematica 51, 631-658.
Liu, X., Zheng, S. and Feng, X.*(2020). Estimation of error variance via ridge regression. Biometrika 107, 481-488.
Dong, C.#, Li, G. and Feng, X.* (2019). Lack-of-fit tests for quantile regression models. Journal of the Royal Statistical Society B 81, 629-648.
Wang, H., Feng, X.* and Dong, C.# (2019). Copula-based quantile regression for longitudinal data. Statistica Sinica 29, 245-264.
Wu, M., Zhu, L., and Feng, X.* (2018). Network-based feature screening with applications to genome data. The Annals of Applied Statistics 12, 1250-1270.
Feng, X. and He, X.* (2017). Robust low-rank data matrix approximations. SCIENCE CHINA Mathematics 60, 189-200.
Feng, X. and Zhu, L.* (2016). Estimation and testing of varying coefficients in quantile regression. Journal of the American Statistical Association 111, 266-274.
Yi, Y., Feng, X., and Huang, Z.* (2014). Estimation of extreme value-at-risk: an EVT approach for quantile GARCH model. Economics Letters 124, 378-381.
Feng, X.*, Sedransk, N., and Xia, J.Q. (2014). Calibration using constrained smoothing with applications to mass spectrometry data. Biometrics 70, 398-408.
Feng, X., Feng, Y., Chen, Y.* and Small, D. S. (2014). Randomization inference for the trimmed mean of effects attributable to treatment. Statistica Sinica 24, 773-797.
Feng, X. and He, X.* (2014). Statistical inference based on robust low-rank data matrix approximation. The Annals of Statistics 42, 190-210.
Wang, H. and Feng, X.* (2012). Multiple imputation for M regression with censored covariates. Journal of the American Statistical Association 107, 194-204.
Feng, X., He, X. and Hu, J.* (2011). Wild bootstrap for quantile regression. Biometrika 98, 995-999.
Feng, X. and He, X.* (2009). Inference on low-rank data matrices with applications to microarray data. The Annals of Applied Statistics 3, 1634-1654.
Wang, X., Liang, D*, Feng, X. and Ye, L. (2007). A derivative free optimization algorithm based on conditional moments. Journal of Mathematical Analysis and Applications 331, 1337-1360.

Methodology (Conference)


Wang, C.# and Feng, X.* (2024). Optimal kernel quantile learning with random features. International Conference on Machine Learning 2024, Vienna, Austria. (Spotlight)
Feng, X., He, X., Wang, C.*#, Wang, C.# and Zhang, J. (2023). Towards a unified analysis of kernel-based methods under covariate shift. Neural Information Processing Systems 2023, New Orleans, USA.
Zhou, F., Wang, J.#, and Feng, X.* (2020). Non-crossing quantile regression for deep reinforcement learning. Neural Information Processing Systems 2020, Vancouver, Canada.
Wu, S.#, Feng, X., and Zhou, F.* (2020). Metric learning by similarity network for deep semi-supervised learning.  14th International FLINS Conference on Robotics and Artificial Intelligence (FLINS/ISKE2020), Cologne, Germany.


Interdisciplinary Studies


Li, X.#, Zhou, T.#, Feng, X.*, Yau, S.-T.*, Yau, S. S.-T.* (2024). Exploring geometry of genome space via Grassmann manifolds. The Innovation 5(5), 100677. (Impact factor: 33.2) Online Link
Abbatiello, S., Mani, D., Schilling, B., Maclean, B., Zimmerman, L., Feng, X. etc. (2013). Design, Implementation, and Multi-Site Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in LC-MRM-MS. Molecular & Cellular Proteomics 12, 2623-2639. (Impact factor: 7.38)
Xia, J.Q., Sedransk, N. and Feng, X. (2011). Variance component analysis of a multi-site study aiming at multiple reaction monitoring measurements of peptides in human plasma. Public Library of Science One 6, e14590. (Impact factor: 3.75)
Broglio, S., Schnebel, B., Sosnoff, J., Shin, S. Feng, X., He, X. and Zimmerman, J. (2010). The biomechanical properties of concussions in high school football. Medicine and Science in Sports and Exercise 42, 2064-2071. (Impact factor: 6.29)
Feng, X., Huang, S., Shou, J., Liao, B., Yingling, J. M., Ye, X., Lin, X., Gelbert, L. M., Su, E. W., Onyia, J. E. and Li, S. (2007). Analysis of pathway activity in primary tumors and NCI60 cell lines using gene expression profiling data. Genomics Proteomics and Bioinformatics 5, 15 - 24. (Impact factor: 9.5)
Xia, Y., Campen, A., Rigsby, D. , Guo, Y., Feng, X., Su, E.W., Dalakal, M. and Li, S. (2007). A Microarray Gene Expression Database for Primary Human Disease Tissues. Molecular Diagnosis and Therapy 11, 145-149. (Impact factor: 3.91)
Note: '#' and '*' refer to students and corresponding authors, respectively.


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