Y. Ma and L.-Z. Liao, ``The Glowinski-Le Tallec splitting method revisited: A general convergence and convergence rate analysis'', JIMO, 17(4), 1681-1711, 2021.

Cheng, M.-Y. (2021). Discussion on ``Estimation of Hilbertian Varying Coefficient Models'' by Young Kyung Lee, Byeong U. Park, Hyerim Hong and Dognwoo Kim, Statistics and Its Interface, in press.

Z. Tang, Z. Fu, M. Chen, and L. Ling. A localized extrinsic collocation method for Turing pattern formations on surfaces. Applied Mathematics Letters. 122:107534. 2021

Dong Li and Tao Tang. Stability of the Semi-Implicit Method for the Cahn-Hilliard Equation with Logarithmic Potentials, Ann. Appl. Math., 37 (2021), pp. 31-60.

Hong-lin Liao, Tao Tang and Tao Zhou. An energy stable and maximum bound preserving scheme with variable time steps for time fractional Allen-Cahn equation, accepted by SIAM J. Sci. Cpmput. (2021).

Hong-lin Liao, Xuehua Song, Tao Tang and Tao Zhou. Analysis of the second-order BDF scheme with variable steps for the molecular beam epitaxial model without slope selection, Sci China Math, 64 (2021), pp. 887–902,.

Zheng, J. S. and Zhu, Lixing (2021). Determining the number of canonical correlation pairs for high dimensional vectors, Annals of Institute of Statistical Mathematics, 73, 737–756

Xie, J. S., Zeng, Y. C. and Zhu Lixing (2021). Limiting laws for extreme eigenvalues of large-dimensional spiked Fisher matrices with a divergent number of spikes, Journal of Multivariate Analysis, 184, 104742

Fan, Y., Liu, Y. and Zhu, Lixing (2021). Optimal subsampling for linear quantile regression models, Canadian Journal of Statistics, online.

Zhou N. W. and Zhu, Lixing (2021). On IPW-based estimation of conditional average treatment effect, Journal of Statistical Planning and Inference, 215, 1-22.

Amina Benabid, Jun Fan and Dao-Hong Xiang. Comparison theorems on large-margin learning, International Journal of Wavelets, Multiresolution and Information Processing, in press, 2021.

Fusheng Lv and Jun Fan. Optimal learning with Gaussians and correntropy loss, Analysis and Applications, 19(01):107-124, 2021.

S. Hon, S. Serra-Capizzano, and A. Wathen, Band-Toeplitz preconditioners for ill-conditioned nonsymmetric Toeplitz systems, to appear, BIT Numerical Methods, 2021.

H. Garcke, K.F. Lam and A. Signori, Sparse optimal control of a phase field tumour model with mechanical effects, SIAM J. Control Optim. 59 (2021) 1555–1580

S. Frigeri, K.F. Lam and A. Signori, Strong well-posedness and inverse identification problem of a non-local phase field tumor model with degenerate mobilities, European Jnl. Appl. Math. (2021)

P. Knopf, K.F. Lam, C. Liu and S. Metzger, Phase-field dynamics with transfer of materials: The Cahn–Hilliard equation with reaction rate dependent dynamic boundary conditions, ESAIM: M2AN 55 (2021) 229–282

Zongliang Hu, Yan Zhou and Tiejun Tong (2021). Meta-analyzing multiple omics data with robust variable selection. Frontiers in Genetics, 12: 656826.

Jiajin Wei, Enxuan Lin, Jiandong Shi, Ke Yang, Zongliang Hu, Xiantao Zeng and Tiejun Tong (2021). Meta-analysis with zero-event studies: a comparative study with application to COVID-19 data. Military Medical Research, 8: 41.

Sanying Feng, Gaorong Li, Heng Peng and Tiejun Tong (2021). Varying-coefficient panel data model with interactive fixed effects. Statistica Sinica, 31: 935-957.

Zongliang Hu, Zhishui Hu, Kai Dong, Tiejun Tong and Yuedong Wang (2021). A shrinkage approach to joint estimation of multiple covariance matrices. Metrika, 84: 339-374.

Wenwu Wang, Wei Shen and Tiejun Tong (2021). Robust estimation of nonparametric function via addition sequence. Journal of Statistical Planning and Inference, 211: 423-438.

Yaping Wang, Bin Liu, Xiuqiong Fu, Tiejun Tong and Zhiling Yu (2021). Efficacy and safety of Si-Jun-Zi-Tang-based therapies for functional (non-ulcer) dyspepsia: a meta-analysis of randomized controlled trials. BMC Complementary and Alternative Medicine, 21: 11.

X. Qian, L.-Z. Liao, and J. Sun, ``A strategy of global convergence for the affine scaling algorithm for convex semidefinite programming'', Math. Prog., 179(1-2), 1-19, 2020.

Zhang, J.-T., Guo, J., Zhou, B., and Cheng, M.-Y. (2020). A simple two-sample test in high dimensions based on L_2 norm. Journal of the American Statistical Association,115, 1011--1027.

S.N. Chiu, L. Ling and M. McCourt. On variable and random shape Gaussian interpolations. Applied Mathematics and Computation. 377: 125159. 2020.

S. Li, and L. Ling. Complex pattern formations by spatial varying parameters. Advances in Applied Mathematics and Mechanics. 12(6): 1327-1352. 2020

M. Chen and L. Ling. Extrinsic Meshless Collocation Methods for PDEs on Manifolds. SIAM Journal on Numerical Analysis. 58(2): 988-1007. 2020

M. Chen and L. Ling. Kernel-based collocation methods for heat transport on evolving surfaces. Journal of Computational Physics. 405: 1091 Haifeng Li, Jun Liu, Li Cui, Haiyang Huang, Xue-Cheng Tai, Volume preserving image segmentation with entropy regularized optimal transport and its applications in deep learning, ournal of Visual Communication and Image Representation, Journal of Visual Communication and Image Representation, 71, 102845, 2020/8/1.

Shi Yan, Xue-Cheng Tai, Jun Liu, Hai-Yang Huang, Convexity Shape Prior for Level Set-Based Image Segmentation Method, IEEE Transactions on Image Processing, 29, 7141-7152, 2020/6/5.

Weina Wang, Chunlin Wu, Xue-Cheng Tai, A Globally Convergent Algorithm for a Constrained Non-Lipschitz Image Restoration Model, Journal of Scientific Computing, 83, 1-29, 2020/3/27.

Fan Jia, Xue-Cheng Tai, Jun Liu, , Nonlocal regularized CNN for image segmentation, Inverse Problems & Imaging, 14(5), 891, 2020.66. 2020.

Hong-lin Liao, Tao Tang and Tao Zhou. On energy stable, maximum-principle preserving, second order BDF scheme with variable steps for the Allen-Cahn equation, SIAM J. Numer. Anal. 58-4 (2020), pp. 2294-2314.

Hong-lin Liao, Tao Tang and Tao Zhou. A second-order and nonuniform time-stepping maximum-principle preserving scheme for time-fractional Allen-Cahn equations, J. Comput. Phys. 414 (2020): 109473.

Chaoyu Quan, T. Tang and Jang Yang, How to Define Dissipation-Preserving Energy for Time-Fractional Phase-Field Equations, CSIAM Transactions on Applied Mathematics 1(2020), pp. 478-490.

Changtao Sheng, Jie Shen, Tao Tang, Li-Lian Wang and Huifang Yuan. Fast Fourier-like mapped Chebyshev Spectral-Galerkin methods for PDEs with integral fractional Laplacian in unbounded domains. SIAM J. Numer. Anal. (2020), pp. 2435-2464.

Tao Tang. Revisit of Semi-Implicit Schemes for Phase-Field Equations, Anal. Theory Appl., 36(3) (2020), 235-242.

Tao Tang and Zhonghua Qiao. Efficient numerical methods for phase-field equations, Science Sinica Mathematica, 50(6) (2020), 1-20.

Tao Tang, Lilian Wang, Huifang Yuan, and Tao Zhou. Rational spectral methods for PDEs involving fractional Laplacian in unbounded domains, SIAM J. Sci. Comput., 42(2) (2020), A585-A611.

J. K. Zhou and Zhu, Lixing (2020). Modified Martingale Difference Correlations, Journal of Nonparametric Statistics, accepted.

Zhu, X. H., Lu, J., Zhang, J. and Zhu Lixing (2020). Testing for conditional independence: a groupwise dimension reduction-based adaptive-to-model approach, Scandinavian Journal of Statistics, accepted.

Wang, T. and Zhu, Lixing (2020). Model-based inverse regression and its applications. accepted by Festschrift in Honor of Dennis, R. Cook

Chen, F., Shi, L., Zhu, L. and Zhu, Lixing (2020). A method of local influence in sufficient dimension reduction, Statistica Sinica, accepted.

Jin, L. B., Chiu, S. N., Zhao, J, H. and Zhu, Lixing (2020). Constrained maximum likelihood estimation for skewed normal mixture models. Sci. in China (In Chinese), in press.

Guo, X., Li, R. Z., Liu, W. J. and Zhu, Lixing (2020). Stable correlation and robust feature screening, Science in China, online (nb).

Deng, K., Jiang, Y. Kai, Liu, J., Zhao, X. S. and Zhu, Lixing (2020). Total-effect Test Is Superfluous for Establishing Mediation in the Classic Mediation Model, Statistica Sinica, accepted.

Yu, W., Xu, W. L. and Zhu, Lixing (2020). Estimating the number of equal components for two highdimensional mean vectors, Communication in Statistics-Theory and Methods, Online.

Xie, C. L. and Zhu, Lixing (2020). Generalized Kernel-based Inverse Regression Methods for Sufficient Dimension Reduction. Computational Statistics and Data Analysis, 150, 106995.

Chan, B. D., Wong, G., Jiang, Q., Lee, M. M., Wong, W. M., Chen, F., Wong, W. T., Zhu, Lixing Wong, K. M. and Tai, C.S. (2020). Longitudinal study of BKV outcomes, risk factors, and kinetics in renal transplantation patients, Microbial Pathogenesis, 142:10403

Zhu, X.H., Guo, X., Wang, T. and Zhu, Lixing(2020). Dimensionality determination in dimension reduction: a thresholding double ridge ratio approach, Computational Statistics and Data Analysis, 146, 106910.

Feng, Z. H., Lin, L. Zhu, R. Q. and Zhu, Lixing (2020). Nonparametric Variable Selection and Its Application to Additive Models, Annals of the Institute of Statistical Mathematics, 72, 827 – 854.

Yunlong Feng, Jun Fan and Johan Suykens. A statistical learning approach to modal regression, Journal of Machine Learning Research, 21(2):1–35, 2020.

Jun Fan and Dao-Hong Xiang. Quantitative convergence analysis of kernel based large-margin unified machines, Communications on Pure and Applied Analysis, 19(8):4069–4083, 2020.

Ting Hu, Jun Fan and Dao-Hong Xiang. Convergence analysis of distributed multi-penalty regularized pairwise learning, Analysis and Applications, 18(1):109–127, 2020.

MJ Gander, F Kwok, J Salomon. PARAOPT: A parareal algorithm for optimality systems. SIAM Journal on Scientific Computing 42 (5), A2773-A2802, 2020

Cheng, Q., Yang, Y., Shi, X., Yang, C., Peng, H. and Liu, J. (2020), MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting linkage disequilibrium and horizontal pleiotropy, NAR Genomics and Bioinformatics, 2(2), lqaa028.

Cai, M., Dai, M., Ming, J., Peng, H., Liu, J. and Yang, C. (2020), BIVAS: A scalable Bayesian method for bi-level variable selection with applications, Journal of Computational and Graphical Statistics, 29, 40-52.

Zhang, J., Cui, X. and Peng, H. (2020), Estimation and hypothesis test for partial single-index multiplicative models, Annals of the Institute of Statistical Mathematics, 72, 699-740.

Jiandong Shi, Dehui Luo, Hong Weng, Xiantao Zeng, Lu Lin, Haitao Chu and Tiejun Tong (2020). Optimally estimating the sample mean and standard deviation from the five-number summary. Research Synthesis Methods, 11: 641-654.

Ke Yang, Hiu-Yee Kwan, Zhiling Yu and Tiejun Tong (2020). Model selection between the fixed-effects model and the random-effects model in meta-analysis. Statistics and Its Interface (Special Issue on Meta-analysis), 13: 501-510.

Jiandong Shi, Tiejun Tong, Yuedong Wang and Marc G. Genton (2020). Estimating the mean and variance from the five-number summary of a log-normal distribution. Statistics and Its Interface (Special Issue on Meta-analysis), 13: 519-531.

Shuwei Li, Tao Hu, Tiejun Tong and Jianguo Sun (2020). Semi-parametric regression analysis of multivariate doubly-censored data. Statistical Modelling, 20: 502-526.

Fengyang He, Huixia Judy Wang and Tiejun Tong (2020). Extremal linear quantile regression with Weibull-type tails. Statistica Sinica, 30: 1357-1377.

Hong Zhang, Tiejun Tong, John Landers and Zheyang Wu (2020). TFisher: A powerful truncation and weighting procedure for combining p-values. Annals of Applied Statistics, 14: 178-201.

Yuejin Zhou, Sze-Yui Ho, Jiahua Liu and Tiejun Tong⋆ (2020). Hypothesis testing for normal distributions: a unified framework and new developments. Statistics and Its Interface, 13: 167-179.

Hailun Wang, Pak Sham, Tiejun Tong and Herbert Pang (2020). Pathway-based single-cell RNA-Seq classification, clustering, and construction of gene-gene interactions networks using random forests. IEEE Journal of Biomedical and Health Informatics, 24: 1814-1822.

Sanying Feng, Gaorong Li, Tiejun Tong and Shuanghua Luo (2020). Testing for heteroskedasticity in two-way fixed effects panel data models. Journal of Applied Statistics, 47: 91-116.

L. M. Sun and L.-Z. Liao, ``An interior point continuous path-following trajectory for linear programming'', JIMO, 15(4), 1517-1534, 2019.

Zhang, J.-T., Cheng, M.-Y., Wu, H.-T, and Zhou, B. (2019). A new test for functional one-way ANOVA with application to ischemic heart screening. Computational Statistics and Data Analysis,132, 3-17.

Yue, M., Li, J., and Cheng, M.-Y. (2019). Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients. Computational Statistics and Data Analysis,131, 222-234.

M. Chen and L. Ling. Kernel-based meshless collocation methods for solving coupled bulk-surface PDEs. Journal of Scientific Computing. 81(1): 375-391. 2019.

S. Li and L. Ling. Collocation methods for Cauchy problems of elliptic operators via conditional stabilities. Communications in Computational Physics. 26(3): 785-808. 2019.

S. Li and L. Ling. Weighted least-squares collocation methods for elliptic PDEs with mixed boundary conditions. Engineering Analysis with Boundary Elements. 105: 146-154. 2019.

P. K. Mishra, G. E. Fasshauer, M .K. Sen and L. Ling. A stabilized radial basis-finite difference (RBF-FD) method with hybrid kernels. Computers and Mathematics with Applications. 77(9): 2354-2368. 2019.

S. Li, L. Ling and K.C. Cheung. Discrete least-squares radial basis functions approximations. Applied Mathematics and Computation. 355: 542-552. 2019.

A. Petras, L. Ling, C. Piret and S. Ruuth. A least-squares implicit RBF-FD closest point method and applications to PDEs on moving surfaces. Journal of Computational Physics. 381: 146-161. 2019.

Liang-Jian Deng, Minyu Feng, Xue-Cheng Tai, The fusion of panchromatic and multispectral remote sensing images via tensor-based sparse modeling and hyper-Laplacian prior, Information Fusion, 52, 76-89, 2019/12/1.

Haixia Liu, Xue-Cheng Tai, Curvature-based authentication of van Gogh paintings, Methods and Applications of Analysis, 26(3), 269-280, 2019/9.

Shousheng Luo, Xue-Cheng Tai, Limei Huo, Yang Wang and Roland Glowinski, , Convex Shape Prior for Multi-Object Segmentation Using a Single Level Set Function, Proceedings of the IEEE International Conference on Computer Vision, 613-621, 2019/10.

Shousheng Luo, Ruyue Meng, Suhua Wei, Jian-Feng Cai, Xue-Cheng Tai, Yang Wang, Data-driven Method for 3D Axis-symmetric Object Reconstruction from Single Cone-beam Projection Data, Proceedings of the Third International Symposium on Image Computing and Digital Medicine, 288-292., 2019/9/24.

Shousheng Luo, Keke Kang, Yang Wang, Xue-Cheng Tai, Low-dose X-ray Computed Tomography Image Reconstruction Using Edge Sparsity Regularization,, Proceedings of the Third International Symposium on Image Computing and Digital Medicine, 303-307, 2019/9/24.

Jia Fan, Xue-cheng Tai, Regularized UNet for Automated Pancreas Segmentation, Proceedings of the Third International Symposium on Image Computing and Digital Medicine,, 113-117, 2019/9/24.

Alexander Malyshev, Xue-Cheng Tai, Variational Model for Depth Estimation from Images,, 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA),, 1-8, 2019/9/26.

LJ Deng, M Feng, XC Tai, The fusion of panchromatic and multispectral remote sensing images via tensor-based sparse modeling and hyper-Laplacian prior, Information Fusion, 52, 76-89, 2019/12/1.

LJ Deng, R Glowinski, XC Tai, A New Operator Splitting Method for the Euler Elastica Model for Image Smoothing, SIAM Journal on Imaging Sciences 12, 12(2), 1190-1230, 2019/6/25.

S Yan, J Liu, H Huang, XC Tai, A dual EM algorithm for TV regularized Gaussian mixture model in image segmentation, Inverse Problems & Imaging, 13(3), 653-677, 2019/3/19.

Y Shi, K Yin, XC Tai, et. al, Evaluation of the performance of classification algorithms for XFEL single-particle imaging data, IUCrJ, 6, 331-340, 2019/3/1.

X He, W Zhu, XC Tai, Segmentation by Elastica Energy with L1 and L2 Curvatures: a Performance Comparison, NUMERICAL MATHEMATICS-THEORY METHODS AND APPLICATIONS, 12(1), 285-311, 2019/2/1.

Zhiwei Fang, Jichun Li, Tao Tang and Tao Zhou, Efficient Stochastic Galerkin Methods for Maxwell's Equations with Random Inputs, J. Sci. Comput., 80(1) (2019), 248-267.

T. Tang, On effective numerical methods for phase-field models, Proceedings of the International Congress of Mathematicians, (ICM 2018), pp. 3669-3690 (2019).

Tao Tang, Haijun Yu and Tao Zhou, On energy dissipation theory and numerical stability for time-fractional phase field equations, SIAM J. Sci. Comput. , 41(6) (2019), A3757-3778.

Tan, F. L., Jiang, X. J., Guo, X. and Zhu, Lixing (2019). Testing heteroscedasticity for regression models based on projections. Statistica Sinica, accepted.

Xie, C. L. and Zhu, Lixing (2019). A Goodness-of-Fit Test for Variable-adjusted Models, Computational Statistics and Data Analysis, 138, 27-48

Tan, F. L., and Zhu, Lixing (2019). Adaptive-to-model checking for regressions with diverging number of predictors, Annals of Statistics, 47, 1960 - 1994.

Koul, H., Xie, C. L. and Zhu, Lixing (2019). An Adaptive-to-Model Test for Parametric Single-Index Errorsin-Variables Models, Statistica Sinica, 29, 1511 – 1534

Li, L. Z., Chiu, S. N. and Zhu, Lixing (2019). Model checking for regressions: an approach bridging between local smoothing and global smoothing methods, Computational Statistics and Data Analysis, 138, 64-82

Yu, W., Xu, W. L. and Zhu, Lixing (2019). A Combined p-value Test for the Mean Difference of High dimensional Data, Science in China: Mathematics, 62, 961 - 978. (b)

Lin, L., Li, F., Wang, K. N. and Zhu, Lixing (2019). Composite Estimation: An Asymptotically Weighted Least Squares Approach, Statistica Sinica, 29, 1367-1393 (b)

Yu,W., Xu,W. L. and Zhu, Lixing (2019). Multiple permutation test for high-dimensional data: a components combined algorithm, Journal of Statistical Computation and Simulation, 89, 686-707

Lu, J. Zhu, X. H., Lin, L. and Zhu, Lixing (2019). Estimation for biased partial linear single index models, Computational Statistics and Data Analysis, 139, 1-13.

Guo, X., Song, L. L, Fang, Y. and Zhu, Lixing (2019). Model checking for general linear regression with nonignorable missing response, Computational Statistics and Data Analysis, 138, 1-12.

Jiang, Q., Huskov, M., Meintanis, S. and Zhu, Lixing (2019). Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data, Journal of Multivariate Analysis, 170, 202-220

Chen, F., Meintanis, S. and Zhu, Lixing (2019). On some characterizations of, and multidimensional criteria for testing homogeneity, symmetry and independence, Journal of Multivariate Analysis, 173, 125-144.

Guo, G. B., Allison, J. and Zhu, Lixing (2019). Bootstrap maximum likelihood for quasi-stationary distributions, Journal of Nonparametrics, 31, 64 - 87.

Chiu, S. N. and Liu, K. I. (2019) Improving p-value approximation and level accuracy of Monte Carlo tests by quasi-Monte Carlo methods. Communications in Statistics—Simulation and Computation. DOI: 10.1080/03610918.2019.1667389

Li, L., Chiu, S. N. and Zhu, L. (2019) Model checking for regressions: an approach bridging between local smoothing and global smoothing methods. Computational Statistics and Data Analysis 138, 64-82.

Jun Fan, Fusheng Lv and Lei Shi. An RKHS approach to estimate individualized treatment rules based on functional predictors. Mathematical Foundations of Computing, 2(2):169-181, 2019.

S. Hon and A. Wathen, Numerical investigation of the spectral distribution of Toeplitz-function sequences, Computational Methods for Inverse Problems in Imaging. Springer INdAM Series, vol 36. Springer, Cham, 2019.

P. Ferrari, I. Furci, S. Hon, M. Mursaleen, and S. Serra-Capizzano, The eigenvalue distribution of special 2-by-2 block matrix sequences, with applications to the case of symmetrized Toeplitz structures, SIAM J. Matrix Anal. Appl. 40(3), 1066-1086, 2019.

S. Hon, M. Mursaleen, and S. Serra-Capizzano, A note on the spectral distribution of symmetrized Toeplitz sequences, Linear Algebra and its Application, 579:32-50, 2019.

S. Hon, Circulant preconditioners for analytic functions of Hermitian Toeplitz matrices, Journal of Computational and Applied Mathematics, 352:328-340, 2019.

ZY Wong, F Kwok, RN Horne. HA Tchelepi, Sequential-implicit Newton method for multiphysics simulation, Journal of Computational Physics 391, 155-178, 2019

F Kwok, BW Ong. Schwarz waveform relaxation with adaptive pipelining, SIAM Journal on Scientific Computing 41 (1), A339-A364, 2019

Feng, S., Li, G., Peng, H. and Tong, T. (2019) Varying coefficient panel data model with interactive fixed effects, Statistica Sinica, accepted.

Wenwu Wang, Ping Yu, Lu Lin and Tiejun Tong (2019). Robust estimation of derivatives using locally weighted least absolute deviation regression. Journal of Machine Learning Research, 20(60): 1-49.

Zongliang Hu, Tiejun Tong and Marc G. Genton (2019). Diagonal likelihood ratio test for equality of mean vectors in high-dimensional data. Biometrics, 75: 256-267.

Yan Zhou, Jiadi Zhu, Tiejun Tong, Junhui Wang, Bingqing Lin and Jun Zhang (2019). A statistical normalization method and differential expression analysis for RNA-seq data between different species. BMC Bioinformatics, 20: 163.

Yanfei Liu, Yingke Zhao, Jinfan Tian, Tiejun Tong, Rui Gao and Yue Liu (2019). The association of depression following percutaneous coronary intervention with adverse cardiovascular events: protocol for a systematic review and meta-analysis. Medicine, 98(2): e13952.

Yiping Yang, Tiejun Tong and Gaorong Li (2019). SIMEX estimation for single-index model with covariate measurement error. AStA Advances in Statistical Analysis, 103: 137-161.

H. Zhu, L.-Z. Liao, and M. K. Ng, ``Multi-instance dimensionality reduction via sparsity and orthogonality'', Neural Comput., 30(12), 3281-3308, 2018.

H. W. Yue, L.-Z. Liao, and X. Qian, ``Two interior point continuous trajectory models for convex quadratic programming with bound constraints'', PJO, 14(3), 527-550, 2018.

H. Zhu, C. Chen, L.-Z. Liao, and M. K. Ng, ``Multiple graphs clustering by gradient flow method'', J. Franklin Institute, 355(4), 1819-1845, 2018.

X. Qian, L.-Z. Liao, J. Sun, and H. Zhu, ``The convergent generalized central paths for linearly constrained convex programming'', SIAM J. Optim., 28(2), 1183-1204, 2018.

X. Qian and L.-Z. Liao, ``Analysis of the primal affine scaling continuous trajectory for convex programming'', PJO, 14(2), 261-272, 2018.

J. Sun, L.-Z. Liao, and B. Rodrigues, ``Quadratic two-stage stochastic optimization with coherent measures of risk'', Math. Prog., B, 168 (1-2), 599-613, 2018.

Cheng, M.-Y., Huang, T., Liu, P., and Peng, H. (2018). Bias reduction for nonparametric and semiparametric regression models. Statistica Sinica, 28, 2749-2770.

Cheng, M.-Y., Feng, S., Li, G., and Lian, H. (2018). Greedy forward regression for variable screening. Australian & New Zealand Journal of Statistics, 60, 20-42.

A. Petras, L. Ling and S. Ruuth. An RBF-FD closest point method for solving PDEs on surfaces. Journal of Computational Physics. 370: 43-57. 2018.

F. L. Yang, L. Yan and L. Ling. Doubly stochastic radial basis function methods. Journal of Computational Physics. 363: 87-97. 2018.

X. Guo and L. Ling. Evaluation finite moment log-stable option pricing by a spectral method. Numerical Mathematics: Theory, Methods and Applications. 11(3): 437-452. 2018.

L. Ling and Q. Ye. On meshfree numerical differentiation. Analysis and Applications. 16(5): 717-739. 2018.

L. Ling and S.N. Chiu. Fully adaptive kernel-based methods. International Journal for Numerical Methods in Engineering. 114(4): 454-467. 2018.

K.C. Cheung and L. Ling. A kernel-based embedding method and convergence analysis for surfaces PDEs. SIAM Journal on Scientific Computing. 40(1), A266-A287. 2018.

K.C. Cheung, L. Ling and R. Schaback. H2-convergence of least-squares kernel collocation methods. SIAM Journal on Numerical Analysis. 56(1): 614-633. 2018.

ZM Boyd, E Bae, XC Tai, AL Bertozzi, Simplified energy landscape for modularity using total variation, SIAM Journal on Applied Mathematics, 78(5), 2439-2464, 2018/9/13.

Z Liu, S Wali, Y Duan, H Chang, C Wu, XC Tai, Proximal ADMM for Euler's elastica based image decomposition model, Numer. Math. Theory Methods Appl., 12(2), 370-402, 2018/9.

L Huo, S Luo, Y Dong, XC Tai, Y Wang, An Iteration Method for X-Ray CT Reconstruction from Variable-Truncation Projection Data, Scale Space and Variational Methods in Computer Vision, 11603, 144-155, 2019/06/05.

LF Li, S Luo, XC Tai, J Yang, A Variational Convex Hull Algorithm, Scale Space and Variational Methods in Computer Vision, 11603, 224-235, 2019/06/05.

Zhubae Egil, Xue-Cheng Tai, Wei, Augmented lagrangian method for an euler's elastica based segmentation model that promotes convex contours., Inverse Problems & Imaging, 11(1), p1-12. 23p, 2017.

Xue-cheng Tai, Jinming Duan, A simple fast algorithm for minimization of the elastica energy combining binary and level set representations, International Journal Of Numerical Analysis And Modeling, 14(6), 809-821, 2017.

Ke Wei, Ke Yin, Xue-Cheng Tai, Tony F. Chan, New region force for variational models in image segmentation and high dimensional data clustering, Annals of Mathematical Sciences and Applications, 3(1), 255 – 286, 2018.

Guanghui Hu, Xucheng Meng and Tao Tang, On Robust and Adaptive Finite Volume Methods for Steady Euler Equations, in "Theory, Numerics and Applications of Hyperbolic Problems II", Springer, 2018, pp. 1-19.

T. Tang and J. Yang, Computing the maximal eigenpairs of large size tridiagonal matrices with O(1) number of iterations, Numer. Math. Theor. Meth. Appl. 11(4) (2018), 877-894.

T. Tang, H. Yuan and T. Zhou, Hermite Spectral Collocation Methods for Fractional PDEs in Unbounded Domains, 10.4208/cicp.2018.hh80.12 Commun. Comput. Phys., 24 (2018), 1143-1168.

Jin, L. B., Xu, W. L., Zhu, L. P., Zhu, L. X. (2018). Penalized Maximum Likelihood Estimation for Skew Normal Mixtures (in Chinese). Sci Sin Math., 48, 1-25

Guo, X. Chan, R., Wong, W. and Zhu, Lixing (2018). Mean-Variance, Mean-VaR, Mean-CVaR models for portfolio selection with background risk, Risk Management, 20, 77 – 94

Chen, F., Shi, L., Zhu, X. H. and Zhu, Lixing (2018). Generalized principal Hessian directions for mixture multivariate skew elliptical distributions, Journal of Multivariate Analysis, 168, 142-159

Niu, C., Guo, X., Li, Y. and Zhu, Lixing (2018). Pairwise Distance-based Tests for Conditional Symmetry, Computational Statistics and Data Analysis, 128, 145-162

Guo, X. and Zhu, Lixing (2018). Semiparametric Double Robust and Efficient Estimation for Mean Response with Missing at Random, Computational Statistics and Data Analysis, 128, 325-339

Xie, C. L. and Zhu, Lixing (2018). A Minimum Projected-Distance Test for Parametric Single-Index Berkson Models. TEST, 27, 700 - 715. (b)

Zhao, J. L, Zhao, H. Y. and Zhu, Lixing (2018). Pivotal variable detection of the covariance matrix and its application to high-dimensional factor models, Statistics and Computing, 28, 775 - 793. (b)

Zhu, X. H. and Zhu, Lixng (2018). Dimension reduction-based significance testing in nonparametric regression, Electronic Journal of Statistics, 12, 1468-1506.

Wang, T. and Zhu, Lixing (2018). Flexible dimension reduction in regression, Statistica Sinica, 28, 1009-1029

Fan, G. L., Liang, H. Y. and Zhu, Lixing (2018). Penalized profile least squares-based statistical inference for varying coefficient partially linear errors-in-variables models. Science in China: Mathematics, 61, 1677-1694.

Niu, C. Z. and Zhu Lixng (2018). A robust adaptive-to-model enhancement test for parametric single-index models, Annals of Institute of Statistical Mathematics, 70, 1013-1045. (b)

Fan, Y., Härdle, W., Wang, W., and Zhu, Lixing (2018). Single index based CoVaR with very high dimensional covariates, the Journal of Business & Economic Statistics, 36, 212-226.(b)

Niu, C., Guo, X. and Zhu, Lixing (2018). Enhancements of nonparametric generalized likelihood ratio test: Bias-correction and dimension reduction, Scand. J. of Stat., 45, 217-254. (b)

Wang, T., Chen, M. J., Zhao, H. and Zhu, Lixing (2018). Estimating a sparse reduction for general regression in high dimensions, Statistics and Computing, 28, 33-46

Tan, F. L., Zhu, X. H. and Zhu, Lixing (2018). A projection-based adaptive-to-model test for regressions. Statistica Sinica, 28, 157 -188.

Guo, X., Wagener, A., Wong, W., and Zhu, Lixing (2018). The two-moment decision model with additive risks, Risk Management, 20, 77-94. (SUIBE)

Shara I. Feld, Jun Fan, Ming Yuan, Yirong Wu, Kaitlin M. Woo, Roxana Alexandridis, and Elizabeth S. Burnside. Utility of Genetic Testing in Addition to Mammography for Determining Risk of Breast Cancer Depends on Patient Age, AMIA Jt Summits Transl Sci Proc., 81-90, 2018.

Yirong Wu, Jun Fan, Peggy Peissig, Richard Berg, Ahmad Pahlavan Tafti, Jie Yin, Ming Yuan, David Page, Jennifer Cox, and Elizabeth S. Burnside. Quantifying predictive capability of electronic health records for the most harmful breast cancer, Proc SPIE Int Soc Opt Eng., 10577:105770J, 2018.

S. Hon, Preconditioning for Toeplitz-related systems, DPhil thesis, University of Oxford, 2018.

S. Hon, Optimal preconditioners for systems defined by functions of Toeplitz matrices, Linear Algebra and its Applications, 548:148-171, 2018.

M. Hammerschmidt, J. Pabisiak, A. Perez-Gea, N. Julian, S. Hon, and S. Burger, Efficient finite-element-based numerical modelling of large sub-wavelength patterned optical structures, Proc. SPIE 10542, High Contrast Metastructures VII, 105421G, 2018.

S. Hon and A. Wathen, Circulant preconditioners for analytic functions of Toeplitz matrices, Numerical Algorithms, 79:1211-1230, 2018.

F Kwok. Numerical methods for spectral theory, Spectral Theory and Applications 720, 101, 2018

MJ Gander, F Kwok. Numerical analysis of partial differential equations using maple and MATLAB, Society for Industrial and Applied Mathematics, 2018

Y Gu, F Kwok. Optimized Schwarz-based Nonlinear Preconditioning for Elliptic PDEs, International Conference on Domain Decomposition Methods, 260-267, 2018

MJ Gander, F Kwok, H Zhang, Multigrid interpretations of the parareal algorithm leading to an overlapping variant and MGRIT, Computing and Visualization in Science 19 (3), 59-74, 2018

Zhang, F. P., Peng, H. and Zhou, Y. (2018), Fine-Gray proportional subdistribution hazards model for competing risks data under length-biased sampling, Statistics and its inference, accepted.

Zhang, J., Feng, Z. H. and Peng, H. (2018), Estimation and hypothesis test for partial linear multiplicative models, Computational Statistics and Data Analysis, 128, 87-103.

Xu, P. R., Peng, H. and Huang, T. (2018), Unsupervised learning of mixture regression models for longitudinal data, Computational Statistics and Data Analysis, 125, 44-56.

Zhao, J. X., Peng, H. and Huang, T. (2018), Variance Estimation for Semiparametric Regression Models by Local Averaging, Test, 27, 453-476.

Cheng, M. Y., Huang, T., Liu, P. and Peng, H. (2018), Bias Reduction for Nonparametric and Semiparametric Regression Models, Statistica Sinica, 28, 2749-2770.

Dehui Luo, Xiang Wan, Jiming Liu and Tiejun Tong (2018). Optimally estimating the sample mean from the sample size, median, mid-range and/or mid-quartile range. Statistical Methods in Medical Research, 27: 1785-1805.

Fengyang He, Yebin Cheng and Tiejun Tong (2018). Nonparametric estimation of extreme conditional quantiles with functional covariate. Acta Mathematica Sinica, English Series, 34: 1589-1610.

Yan Zhou, Xiang Wan, Baoxue Zhang and Tiejun Tong (2018). Classifying next-generation sequencing data using a zero-inflated Poisson model. Bioinformatics, 34: 1329-1335.

Yuejin Zhou, Yebin Cheng, Wenlin Dai and Tiejun Tong (2018). Optimal difference-based estimation for partially linear models. Computational Statistics, 33: 863-885.

Wenlin Dai, Yuejin Zhou and Tiejun Tong (2018). Testing discontinuities in nonparametric regression. Journal of Applied Statistics, 45: 450-473.

Yingke Zhao, Branda Yee-Man Yu, Yanfei Liu, Tiejun Tong and Yue Liu (2018). Weight reduction and cardiovascular benefits: Protocol for a systematic review and meta-analysis. Medicine, 97(50): e13246.

X. B. Gao and L.-Z. Liao, A novel neural network for generally constrained variational inequalities, IEEE TNNLS, 28 (9), 2062-2075, 2017.

H. Zhu, X. Zhang, D. Chu, and L.-Z. Liao, ``Nonconvex and nonconvex optimization with generalized orthogonality constraints: an approximate augmented Lagrangian method'', J. Sci. Comput. 72, 331-372, 2017.

X. Qian, L.-Z. Liao, and J. Sun, ``Analysis of some interior point continuous trajectories for convex programming'', Optimization, 66 (4), 589-608, 2017.

K.C. Cheung and L. Ling. Convergence studies for an adaptive meshless least-squares collocation method. International Journal of Computational Methods and Experimental Measurements. 5(3): 377-386. 2017.

K.C. Cheung and L. Ling. Meshless collocation methods with graph Laplacian for PDEs on folded surface. Neural, Parallel, and Scientific Computations. 25: 79-90. 2017.

Z. J. Fu, Q. Xi, L. Ling and C.-Y. Cao. Numerical investigation on the effect of tumor on the thermal behavior inside the skin tissue. International Journal of Heat and Mass Transfer. 108, Part A, 1154–1163. 2017.

X. Yang, W. Chen, R. Xiao and L. Ling. A fractional model for time-variant non-Newtonian flow. Thermal Science. 21(1A): 61-68. 2017.

Jing Yuan, Ke Yin, Yi-Guang Bai, Xiang-Chu Feng, Xue-Cheng Tai, Bregman-Proximal Augmented Lagrangian Approach to Multiphase Image Segmentation, International Conference on Scale Space and Variational Methods in Computer Vision, 524-534, 2017, Conference Proceeding.

Ke Yin, Xue-Cheng Tai, An effective region force for some variational models for learning and clustering, Journal of Scientific Computing, 74(1), 175-196, 2018.

Hei-Long Chan, Shi Yan, Lok-Ming Lui, Xue-Cheng Tai, Topology-Preserving Image Segmentation by Beltrami Representation of Shapes, Journal of Mathematical Imaging and Vision, 60(3), 401-421, 2018.

E Bae, XC Tai, W Zhu, Augmented lagrangian method for an euler's elastica based segmentation model that promotes convex contours, Inverse Problems and Imaging, 11(1), 1-23, 2017.

Xue-cheng Tai, Jinming Duan, A simple fast algorithm for minimization of the elastica energy combing binary and level set representations, International Journal of Numerical analysis and modelling, 2017, to appear.

K Yin, XC Tai, An effective region force for some variational models for learning and clustering, Journal of Scientific Computing, 1-21, 2017, online publication.

B. Gong, W. Liu, T. Tang, W. Zhao, and T. Zhou, An efficient gradient projection method for Stochastic optimal control problems, SIAM J. Numer. Anal. 55(6) (2017), 2982-3005.

Li, Z. X., Chen, F. and Zhu, Lixing (2017). Estimating moments in ANOVA-type mixed models, Metrika, 80, 697 - 715. (suibe)

Ka-Kit Chua, Adrian Wong, Kam Wa Chan, Yin-Kei Lau, Zhao Xiang Bian, Jia-Hong Lu, Liang-Feng Liu, Lei-Lei Chen, Ka-Ho Chan, Kim-Pong Tse, Anne Chan, Juxian Song, Justin CY Wu, Lixing Zhu, Vincent C. Mok and Min Li (2017). A Randomized Controlled Trial of Chinese Medicine on Non-motor Symptoms in Parkinson’s Disease. Parkinson’s Disease, (IF 1.722), Article ID 1902708, 8 pages.

Alghalith, M., Guo, X., Wong, W. K. and Zhu, Lixing (2017). Input Demand under Joint Energy and Output Prices Uncertainties, Asia-Pacific Journal of Operational Research, 34, 1750018 (2017) (b)

Wong, W. K., Guo, X. and Zhu, Lixing (2017). A Bayesian Approach to Excess Volatility, Short-term Underreaction and Long-term Overreaction during Financial Crises, North American Journal of Economics and Finance, 42, 346-358. (b)

Dai,W. L., Tong, T. J. and Zhu, Lixing (2017). Optimal sequence or ordinary sequence? A unified framework for variance estimation in nonparametric regression, Statistical Science, 32, 455-468.

Zeng, B., Wen, X. R. and Zhu, Lixing (2017). A link-free sparse group variable selection method for single index model, Journal of Applied Statistics, 44, 2388-2400.

Guo, X. and Zhu, Lixing (2017). A review on dimension-reduction based tests for regressions, From Statistics to Mathematical Finance, Festschrift in Honour of Winfried Stute, 105-128, Springer.

Gai, Y. J., Li, F., Yin, Z., Lin, L. and Zhu, Lixing (2017). Asymptotics for adaptive Dantzig selector. Science in China: Mathematics, 47, 869-886. In Chinese, (s)

Feng, L., Zou, C. L., Wang, Z. J. and Zhu, Lixing (2017). Composite T2 test for high-dimensional data, Statistica Sinica, 27, 1419-1436

Lin, L., Dong, P., Song, Y. and Zhu, Lixing (2017). Upper Expectation Parametric Regression, Statistica Sinica, 27, 1265-1280

Zhu, X. H., Guo, X. and Zhu, Lixing (2017). An adaptive-to-model test for partially parametric single-index models, Statistics and Computing, 27, 1193-1204 (b).

Niu, C. Z. and Zhu, Lixing (2017). An adaptive-to-model test for parametric single-index models with missing responses. Electronic Journal of Statistics, 11, 1491 - 1526. (b)

Wu P., Luo X. C., Xu P. R. and Zhu Lixing (2017). New variable selection for linear mixed-effects models. Annals of Institute of Statistical Mathematics, 69, 627-646. (b)

Guan, Y., Xie, C.L. and Zhu, Lixing (2017). Sufficient dimension reduction with mixture multivariate skew elliptical distributions, Statistica Sinica, 27, 335-355.

Wang, T., Wen, X. R. and Zhu, Lixing (2017). Multiple-population Shrinkage Estimation via Sliced Inverse Regression, Statistics and Computing, 27, 103-114 (b)

Yu, W., Xu, W. L. and Zhu,Lixing (2017). A Modified Hosmer-Lemeshow Test for Large Data Sets, Communications in Statistics: Theory and Methods, 46, 11813-11825 (s)

Zhu, X. H., Wang, T., Zhao, J. L. and Zhu, Lixing (2017). Inference for biased transformation models. Computational Statistics and Data Analysis, 109, 105-120 (b).

Yulong Zhao, Jun Fan and Lei Shi. Learning rates for regularized least squares ranking algorithm. Analysis and Applications, 15(6):815-836, 2017.

E. McDonald, S. Hon, J. Pestana, and A. Wathen, Preconditioning for nonsymmetry and time-dependence, pages 81-91. Springer International Publishing, Cham, 2017.

MJ Gander, F Kwok, BC Mandal. Convergence of substructuring methods for elliptic optimal control problems, International Conference on Domain Decomposition Methods, 291-300, 2017

R Haynes, F Kwok, Discrete analysis of domain decomposition approaches for mesh generation via the equidistribution principle, Mathematics of Computation 86 (303), 233-273, 2017

Lu, Y., Peng, H., Zhao, J. Deng, Z., Huang, J. Zhang, J., Deng, J., Wang, Z. and Wei, C. (2017), Ubiquitous blood pressure monitoring using EEG and PPG signals, UbiComp, 17 Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, 257-260.

Cui, X., Lu, Y. and Peng, H. (2017), Application of Partial Consistency to Partially Linear Regression Model, Computational Statistics and Data Analysis, 115, 103-121.

Yan, F., Zhang, C. Q. and Peng, H. (2017), Optimal Designs for Additive Mixture Model with Heteroscedastic Errors, Communications in Statistics - Theory and Methods, 46, 6401-6411.

Huang, T., Peng, H. and Zhang, K. (2017), Model Selection for Gaussian Mixture Models, Statistica Sinica, 27, 149-169.

Wenlin Dai, Tiejun Tong and Lixing Zhu (2017). On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression. Statistical Science, 32: 455-468.

Yan Zhou, Baoxue Zhang, Gaorong Li, Tiejun Tong and Xiang Wan (2017). GD-RDA: A new regularized discriminant analysis for high dimensional data. Journal of Computational Biology, 24: 1099-1111.

Zongliang Hu, Kai Dong, Wenlin Dai and Tiejun Tong⋆ (2017). A comparison of methods for estimating the determinant of high-dimensional covariance matrix. International Journal of Biostatistics, 13: 20170013.

Baohong Yuan, Ruhong Li,Weiping Yuan, Tian Yang, Tiejun Tong, Ningfu Peng, Lequn Li, Jianhong Zhong (2017). Harms and benefits of adoptive immunotherapy for postoperative hepatocellular carcinoma: an updated review. Oncotarget, 8: 18537-18549.

Yong Yuan, Tiejun Tong, Xiaoxi Zeng, Yushang Yang, Ziqiang Wang, Yuncang Wang, Junhe Gou and Longqi Chen (2017). Longitudinal study of esophageal mu- cosal damage after esophagectomy and gastric interposition: relationship between reflux-related mucosal injury and Notch signaling. Journal of Thoracic Disease, 9, 5249-5260.

Yujie Li, Gaorong Li and Tiejun Tong (2017). Sequential profile Lasso for ultra-high dimensional partially linear models. Statistical Theory and Related Fields, 1: 234-245.

Yujie Li, Gaorong Li, Heng Lian and Tiejun Tong (2017). Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models. Journal of Multivariate Analysis, 155: 133-150.

H. Wang, R. Li, and T. Tang, Efficient computation of dentritic growth with r-adaptive finite element methods, J. Comput. Phys. 227 (2008), 5984-6000.

Yana Di, Ruo Li, and T. Tang, A general moving mesh framework in 3D and its application for simulating the mixture of multi-phase flows, Commun. Comput. Phys. 3 (2008), 582-602.

L. Yuan and T. Tang, Resolving the shock-induced combustion by an adaptive mesh redistribution method, J. Comput. Phys. 224 (2007), 587-600.

L. G. Xue and L. X. Zhu, Empirical likelihood for a varying coefficient model with longitudinal data, to appear in J. Amer. Statist. Assoc., 2007.

L. G. Xue and L. X. Zhu, Empirical likelihood semiparametric regression analysis for longitudinal data, to appear in Biometrika, 2007.

G. L. Tian, J. W. Yu, M. L. Tang, and Z. Geng, A new non-randomized model for analyzing sensitive questions with binary outcomes, Statistics in Medicine 26 (2007), 4238-4252.

H. Fu, M. Ng, and J. Barlow, Structured total least squares for color image restoration, SIAM J. Sci. Comput. 28 (2007), 1100-1119.

Z. Bai, G. Golub, and M. Ng, On inexact Hermitian and skew-Hermitian splitting methods for non-Hermitian positive definite linear systems, to
appear in Linear Algebra Appl., 2007.

L. X. Zhu and L. G. Xue, Empirical likelihood confidence regions in a partially linear single-index model, J. Roy. Statist. Soc. B 68 (2006), 549-570.

Chuanju Xu and T. Tang, Stability analysis of large time-stepping methods for epitaxial growth models, SIAM J. Numer. Anal. 44 (2006), 1759-1779.

L. Ling, Y. C. Hon, M. Yamamoto, and T. Takeuchi, Identification of source locations in two-dimensional heat equations, Inverse Problems 22 (2006), no. 4, 1289-1305.

G. H. Golub and L. Z. Liao, Continuous methods for extreme and interior eigenvalue problems, Linear Algebra Appl. 415 (2006), 31-51.

H. Fu, M. Ng, M. Nikolova, and J. L. Barlow, Efficient minimization methods of mixed l1-l1 and l2-l1 norms for image restoration, SIAM J. Sci. Comput. 27 (2006), 1881-1902.

K. T. Fang, Dietmar Maringer, Yu Tang, and Peter Winker, Lower bounds and stochastic optimization algorithms for uniform designs with three or four levels, Math. Comp. 75 (2006), 859-878.

Yana Di, Ruo Li, T. Tang, and Pingwen Zhang, Moving mesh methods for singular problems on a sphere using perturbed harmonic mappings, SIAM J. Sci. Comput. 28 (2006), 1490-1508.

M. Benzi and M. Ng, Preconditioned iterative methods for weighted toeplitz least squares problems, SIAM J. Matrix Anal. Appl. 27 (2006), 1106-1124.

Aijun Zhang, K. T. Fang, Runze Li, and Agus Sudjianto, Majorization framework for balanced lattice designs, The Annals of Statistics 33 (2005), 2837-2853.

Z. Yin, Li Yuan, and T. Tang, A new parallel strategy for two-dimensional incompressible flow simulations using pseudo-spectral methods, J. Comput. Phys. 210 (2005), 325-341.

X. Wu and J. Jin, A finite element method for stokes equations using discrete singularity expansion, Comput. Methods Appl. Mech. Engrg. 194
(2005), 83-101.

M. L. Tang, Nian-Sheng Tang, and Siu-Fung Chan, Confidence interval construction for proportion difference in small-sample paired studies,
Statistics in Medicine 24 (2005), 3565-3579.

K. T. Fang, Yu Tang, and Jianxing Yin, Lower bounds for wrap-around L2-discrepancy and constructions of symmetrical uniform designs, J.
Complexity 21 (2005), 757-771.

Boris N. Azarenok and T. Tang, Second-order Godunov-type scheme for reactive flow calculations on moving meshes, J. Comput. Phys. 206 (2005), 48-80.

X. Wu, B. P. B. Silva, and J. Y. Yuan, Conjugate gradient method for rank deficient saddle point problems, Numer. Algorithms 35 (2004), 139-154.

Z. Tan, Z. Zhang, Y. Huang, and T. Tang, Moving mesh methods with locally varying time steps, J. Comput. Phys. 200 (2004), 347-367.

W. B. Liu, H. P. Ma, T. Tang, and N. Yan, A posteriori error estimates for DG time-stepping method for optimal control problems governed by parabolic equations, SIAM J. Numer. Anal. 42 (2004), no. 3, 1032-1061.

Y. Q. Huang, Zhong-Ci Shi, T. Tang, and W. M. Xue, A multilevel successive iteration methods for nonlinear elliptic problems, Math. Comp. 73 (2004), no. 246, 525-539.

F. J. Hickernell, I. H. Sloan, and G. W. Wasilkowski, On strong tractability of weighted multivariate integration, Math. Comp. 73 (2004), 1903-1911.

S. Heinrich, F. J. Hickernell, and R. X. Yue, Optimal quadrature for Haar wavelet spaces, Math. Comp. 73 (2004), 259-277.

X. B. Gao, L. Z. Liao, and W. M. Xue, A neural network for a class of convex quadratic minimax problems with constraints, IEEE Trans. Neural Networks 15 (2004), no. 3, 622-628.

K. T. Fang and G. N. Ge, A sensitive algorithm for detecting the inequivalence of Hadamard matrices, Math. Comp. 73 (2004), no. 246, 843-851.

Q. Y. Chen, T. Tang, and Z. H. Teng, A fast numerical method for integral equations of the first kind with logarithmic kernel using mesh grading, J. Comput. Math. 22 (2004), no. 2, 287-298.

S. Y. Cheng, C.-W. Shu, and T. Tang (eds.), Recent advances in scientific computing and partial differential equations, AMS Series in Contemporary Mathematics, vol. 330, American Mathematical Society, Providence, Rhode Island, 2003.

S. N. Chiu, Spatial point pattern analysis by using Voronoi diagrams and Delaunay tessellations -- a comparative study, Biometrical J. 45 (2003), no. 3, 367-376.

B. S. He, L. Z. Liao, and S. L. Wang, Self-adaptive operator splitting methods for monotone variational inequalities, Numer. Math. 94 (2003), no. 4, 715-737.

F. J. Hickernell and H. Niederreiter, The existence of good extensible rank-1 lattices, J. Complexity 19 (2003), 286-300.

K. T. Fang, D. K. J. Lin, and H. Qin, A note on optimal foldover design, Statist. Prob. Letters 62 (2003), 245--250.

K. T. Fang, X. Lu, and P. Winker, Lower bounds for centered and wrap-around l2-discrepancies and construction of uniform designs by the threshold accepting, J. Complexity 19 (2003), no. 5, 692-711.

C. X. Ma, K. T. Fang, and D. K. J. Lin, A note on uniformity and orthogonality, J. Statist. Plan. Infer. 113 (2003), 323--334.

H. Z. Tang and T. Tang, Adaptive mesh method for one- and two-dimensional hyperbolic conservation law, SIAM J. Numer. Anal. 41 (2003), no. 2, 487-515.

H. Z. Tang, T. Tang, and P. W. Zhang, An adaptive mesh redistribution method for nonlinear hamilton-jacobi equations in two and three dimensions, J. Comput. Phys. 188 (2003), 543--572.

T. Tang, Z.-H. Teng, and Z.-P. Xin, Fractional rate of convergence for viscous approximation to nonconvex conservation laws, SIAM J. Math. Anal. 35 (2003), no. 1, 98-122.

X. Wu and W. Xue, Discrete boundary conditions for elasticity problems with singularities, Comp. Meth. Appl. Mech. Eng. 192 (2003), 3777--3795.

K. T. Fang, Theory, method and applications of the uniform design, International J. Reliability, Quality, and Safety Engineering 9 (2002), 305--315.

K. T. Fang, C. X. Ma, and R. Mukerjee, Uniformity in fractional factorials, Monte Carlo and Quasi-Monte Carlo Methods 2000 (K. T. Fang, F. J. Hickernell, and H. Niederreiter, eds.), Springer-Verlag, Berlin, 2002, pp. 232--241.

K. T. Fang and H. Qin, A note on construction of nearly uniform designs with large number of runs, Statist. Prob. Letters 61 (2002), 215--224.

J. C.-M. Fok, B.-Y. Guo, and T. Tang, Combined Hermite spectral-finite difference method for the Fokker-Planck equations, Math. Comp. 71 (2002), 1497--1528.

F. J. Hickernell and M. Q. Liu, Uniform designs limit aliasing, Biometrika 89 (2002), 893--904.

R. Li, W.-B. Liu, H. P. Ma, and T. Tang, Adaptive finite element approximation for distributed elliptic optimal control problems, SIAM J. Control Optim. 41 (2002), 1321--1349.

R. Li, T. Tang, and P.-W. Zhang, A moving mesh finite element algorithm for singular problems in two and three space dimensions, J. Comput. Phys. 177 (2002), 365--393.

C. L. Mei and W. X. Zhang, Testing for linear regression relationgship based on lacally weighted techniques, J. Systems Sci. Math. Sci. 22 (2002), 467--480 (Chinese).

J. X. Pan and K. T. Fang, Growth curve models and statistical diagnostics, Springer, New York, 2002.

G.-H. Golub, X.-Wu, and J.-Y. Yuan, Sor-like methods for augmetned systems, BIT 41 (2001), 71--85.

Y. X. Kan, T. Tang, and Z. H. Teng, On the piecewisely smooth solutions to non-homogeneous scalar conservation laws, J. Differential Equations 175 (2001), 27--50.

R. Li, T. Tang, and P.-W. Zhang, Moving mesh methods in multiple dimensions based on harmonic maps, J. Comput. Phys. 170 (2001), 562--588.

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