When Statistics Embraces A.I.

Purdue Department of Statistics
Home ยป Selected Publications

Selected Journal and Conference Publications

  • Qiu, Y. and Wang, X. (2023). Effcient Multimodal Sampling via Tempered Distribution Flow. JASA. In press.
  • Yang, J., Wang, X., Liu, C. (2023). Partial Conditioning for Inference of Many-Normal-Means with Holder Constraints. International Journal of Approximate Reasoning. In press.
  • Kim, J. and Wang, X. (2022). Robust sensible adversarial learning of deep neural networks for image classification. Annals of Applied Statistics. In press.
  • Wang, X., Liu, Y., and Zhu, H. (2021). Functional finite mixture regression models. Statistica Sinica, accepted.
  • Chen, Y., Gao, Q., and Wang, X. (2021). Inferential Wasserstein GANs. JRSSB. In press.
  • Liu, Y., Li, K., and Wang, X. (2021). A nonlinear sparse neural ODE model for multiple functional processes. Canadian Journal of Statistics. In press.
  • Gao, Q. and Wang, X. (2021). Theoretical Investigation of Generalization Bounds for Adversarial Learning for Deep Neural Networks. Journal of Statistical Theory and Practice. In press.
  • Zhang, Z., Wang, X., Kong, L. and Zhu, H. (2020). High-Dimensional Spatial Quantile Function-on-Scalar Regression. Journal of American Statistical Association. https://doi.org/10.1080/01621459.2020.1870984.
  • Xu, Y. and Wang, X. (2020). Weight Normalized Deep Neural Networks. STAT. DOI: 10.1002/sta4.344.
  • Kim. J., Zhu, H., Wang, X., Do, K. (2020). Scalable network estimation with $L_0$ penalty. Statistical Analysis and Data Mining. In press.
  • Qiu, Y. and Wang, X. (2020). ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion. Journal of the American Statistical Association.  https://doi.org/10.1080/01621459.2019.1691563.
  • Chen, Y., Gao, Q., Liang, F., Wang, X. (2020). Deep Feature Selection via Deep Neural Networks. (Winner of the 2019 ASA SLDS Student Paper Award.) Journal of Computational and Graphical Statistics. In press.
  • Shu, H.,Wang, X., and Zhu, H. (2020). D-CCA: A Decomposition-based Canonical Correlation Analysis for High-Dimensional Datasets. Journal of the American Statistical Association. 115, 292-306.
  • Ren, M., Xu, Y., Lin, Y., Yang, Z. and Wang, X. (2019). Sparse Deep Neural Networks using $L_{1,\inf}$ Weight Normalization. Statistica Sinica. DOI 10.5705/ss.202018.0468.
  • Sun, X., Pang, D., Wang, X., and Ma, P. (2018). Optimal penalized function-on-function regression under a reproducing kernel Hilbert space. Journal of the American Statistical Association, 113, 1601-1611.
  • Chen, Y., Wang, X., Jung, Y., Abedi, V., Zand, R., Bikak, M. Adibuzzaman, M. (2018). Classification of short single lead electrocardiograms (ECGs) for atrial fibrillation detection using piecewise linear spline and XGBoost. Physiological Measurement, 39(10):104006.
  • Lebair, T., Shen, J., and Wang, X. (2017). Minimax lower bound and optimal estimation of convex functions in the sup-norm. IEEE Transactions on Automatic Control, 62 3482-3487.
  • Wang, X. and Zhu, H. (2017). Generalized scalar-on-image regression models via total variation. Journal of the American Statistical Association, 112, 1156-1168.
  • Qu, S., Wang, J.L. and Wang, X. (2016). Optimal estimation for the functional Cox model. Annals of Statistics, 44, 1708-1738.
  • Wang, X. and Ruppert, D. (2015). Optimal prediction in an additive functional model. Statistica Sinica, 25, 567-590.
  • Du, P. and Wang, X. (2014). Penalized likelihood functional regression. Statistica Sinica, 24, 1017-1041.
  • Wang, X. and Shen, J. (2013). Uniform convergence and rate adaptive estimation of convex functions via constrained optimization. SIAM Journal of Control and Optimization, 51, 2753-2787.
  • Wang, X., Du, P. and Shen, J. (2013). Smoothing splines with varying smoothing parameter. Biometrika, 100, 955-970.
  • Choi, I., Li, B. and Wang, X. (2013). Nonparametric estimation of spatial and space-time covariance function. Journal of Agricultural, Biological, and Environmental Statistics, 4, 611-630.
  • Shen, J. and Wang, X. (2011). Estimation of Monotone Functions via P-Splines: A Constrained Dynamical Optimization Approach, SIAM Journal on Control and Optimization, 49, 646-671.
  • Cheng, G. and Wang, X. (2011). Semiparametric additive transformation model under current status data. Electronic Journal of Statistics, 5, 1735-1764.
  • Wang, X., Shen, J. and Ruppert, D. (2011). On the Asymptotics of penalized spline smoothing. Electronic Journal of Statistics, 5, 1-17.
  • Wang, X. and Shen, J. (2010) A Class of Grouped Brunk Estimators and Penalized Spline Estimators for Monotone Regression. Biometrika, 97, 585-601.
  • Wang, X. and Xu, D. (2010). An Inverse Gaussian Process Model for Degradation Data. Technometrics, 52, 188-197.
  • Wang, X. (2010). Wiener Processes with Random Effects for Degradation Data. Journal of Multivariate Analysis, 101, 340-351.
  • Wang, X. (2009). Semiparametric Inference on a Class of Wiener Processes. Journal of Time Series Analysis, 30, 179-207.
  • Wang, X. (2009). Nonparametric Estimation of the Shape Function in a Gamma Process for Degradation Data. Canadian Journal of Statistics, 37. 101-118.
  • Wang, X., Walker, M., Pal, J., Woodroofe, M., Mateo, M. (2008) Model-Independent Estimation of Dark Matter Distributions, Journal of the American Statistical Association, 103, 1070-1084.
  • Wang, X. (2008). A Pseudo-Likelihood Estimation Method for Nonhomogeneous Gamma Process Model with Random Effects. Statistica Sinica, 18, 1153-1163.
  • Wang, X. (2008). Bayesian Free-knot Monotone Cubic Spline Regression. Journal of Computational and Graphical Statistics, 17, 373-387.
  • Wang, X. and Li, F. (2008). Isotonic Smoothing Spline Regression. Journal of Computational and Graphical Statistics, 17, 21-37.
  • Wang, X. and Woodroofe, M. (2007) A Kiefer Wolfowitz Comparison Theorem for Wichsell's Problem, Annals of Statistics, 35, 1559-1575.
  • Walker, M., Mateo, M., Olszewskia,E., Gnedini, O., Wang, X., Sen, B, Woodroofe, M. (2007) Velocity Dispersion Profiles of Seven Dwarf Spheroidal Galaxies. Astrophysical Journal Letters, 667, L53-L56.
  • Walker, M., Mateo, M., Olszewski, E., Wang, X. and Woodroofe M. (2006). Radial Velocity Dispersion Profile in the Fornax Dwarf Spheroidal Galaxy. The Astronomical Journal, 131, 2114-2139.
  • Wang, X., Woodroofe, M., Walker, M., Mateo, M. and Olszewski, E. (2005). Estimating Dark Matter Distributions. The Astrophysical Journal, 626, 145-158.

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  • Qiu, Y. and Wang, X. (2020). Stochastic approximate gradient descent via the Langevin algorithm. AAAI 2020. (acceptance rate 20.6%)
  • Wan, C., Jia, D. Zhao, Y., Chang, W., Cao, S., Wang, X., and Zhang, C. (2020). A data denoising approach to optimize functional clustering of single cell RNA-sequencing data. IEEE International Conference on Bioinformatics and Biomedicine 2020 (IEEE BIBM 2020). (acceptance rate 19.4%)
  • Liu, J., Zhang, X., Goldwasser, D. and Wang, X. (2020). Cross-Lingual Document Retrieval with Smooth Learning. The 28th International Conference on Computational Linguistics (COLING 2020). (acceptance rate 32.9%) .
  • Qiu, Y. and Wang, X. (2020). Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models. ICLR 2020. (Spotlight top 6%)
  • Mo, Z., Chen, H., Yang, Z. and Wang, X. (2019). Theoretical Investigation of Generalization Bound for Residual Networks. International Joint Conference on Artifical Intellegence (IJCAI) 2019. (acceptance rate 17.9%)
  • Xu, Y. and Wang, X. (2018). Understanding Weight Normalized Deep Neural Networks with Rectied Linear Units. NeurIPS, 130-139. (acceptance rate 20.8%)
  • Xu, Y., Jean, F., and Wang, X. (2018). On the statistical eciency of compositional nonparametric prediction. AISTAT, 1531-1539. (acceptance rate 33%)
  • Shen, J. and Wang, X. (2012). Convex Regression via Penalized Splines: A Complementarity Approach. 2012 American Control Conference, Montreal, Canada, June, 2012.
  • Shen, J. and Wang, X. (2011). A Constrained Optimal Control Approach to Smoothing Splines, 50th IEEE Conference on Decision and Control, 1729-1734, Orlando, FL, December, 2011.
  • Shen, J. and Wang, X. (2010). Estimation of Shape Constrained Functions in Dynamical Systems and its Applications to Genetic Networks, 2010 American Control Conference, Baltimore, MD.