{"id":9,"date":"2015-08-31T20:45:41","date_gmt":"2015-09-01T00:45:41","guid":{"rendered":"http:\/\/math.cos.ucf.edu\/tengz\/?page_id=2"},"modified":"2024-04-24T16:43:30","modified_gmt":"2024-04-24T20:43:30","slug":"homepage","status":"publish","type":"page","link":"https:\/\/sciences.ucf.edu\/math\/tengz\/","title":{"rendered":"Homepage"},"content":{"rendered":"<p><code><\/code>Associate Professor, Department of Mathematics<\/p>\n<p><span style=\"font-size: medium\">Email: Teng.Zhang@ucf.edu<br \/>\n<\/span><span style=\"font-size: medium\">Office: MSB building 202G<\/span><\/p>\n<p><a href=\"https:\/\/scholar.google.com\/citations?hl=en&amp;user=NZC9xC4AAAAJ&amp;view_op=list_works&amp;sortby=pubdate\">Google scholar<\/a><\/p>\n<hr size=\"2\" width=\"100%\" \/>\n<p><b><span style=\"font-size: large\">Publications:<\/span><\/b><\/p>\n<h3><b><span style=\"font-size: medium\">Monograph:<\/span><\/b><\/h3>\n<ul>\n<li><a href=\"http:\/\/dx.doi.org\/10.1561\/2000000053\">Structured Robust Covariance Estimation<\/a>, Ami Wiesel and Teng Zhang, Foundations and Trends in Signal Processing: Vol. 8: No. 3, pp 127-216, 2015.<\/li>\n<\/ul>\n<div><span style=\"font-size: medium\"><b>Manuscripts:<\/b><\/span><\/div>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2403.18658\">Theoretical Guarantees for the Subspace-Constrained Tyler&#8217;s Estimator.<\/a> Gilad Lerman, Feng Yu, and Teng Zhang.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2403.02704\">Projected Gradient Descent Algorithm for Low-Rank Matrix Estimation<\/a>. Teng Zhang and Xing Fan.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2304.06326\">Understanding Overfitting in Adversarial Training via Kernel Regression<\/a>. Teng Zhang and Kang Li.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2212.14194\">Theoretical Guarantees for Sparse Principal Component Analysis based on the Elastic Net,<\/a> Teng Zhang, Haoyi Yang, and Lingzhou Xue.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1908.02370\">An Algorithm for Graph-Fused Lasso Based on Graph Decomposition<\/a>. Feng Yu, Yi Yang, and Teng Zhang.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1704.07969\">Anisotropic twicing for single particle reconstruction using autocorrelation analysis<\/a>. Tejal Bhamre, Teng Zhang, and Amit Singer.<\/li>\n<\/ul>\n<p><b><span style=\"font-size: medium\">Journal Papers:<\/span><\/b><\/p>\n<ul>\n<li><a href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/10485252.2024.2313137\">Robust Sufficient Dimension Reduction via a-Distance Covariance<\/a>. Hsin-Hsiung Huang, Feng Yu, and Teng Zhang. Journal of Nonparametric Statistics, accepted.<\/li>\n<li><a href=\"https:\/\/link.springer.com\/article\/10.1007\/s11222-023-10318-z?error=cookies_not_supported&amp;code=fcf270f5-2e1f-449c-a119-aa357eb49fda\">A framework of regularized low-rank matrix models for regression and classification<\/a>. Hsin-Hsiung Huang, Feng Yu, Xing Fan, and Teng Zhang. Statistics and Computing, 34(10), 2024.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2203.04369\">Element-wise estimation error of generalized fused lasso<\/a>. Teng Zhang and Sabyasachi Chatterjee. Bernoulli, 29(4): 2691-2718, 2023.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2102.10226\">ALMA: Alternating Minimization Algorithm for Clustering Mixture Multilayer Network<\/a>. Xing Fan, Marianna Pensky, Feng Yu, Teng Zhang. Journal of Machine Learning Research, 23 (1): 14855-14900, 2022.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2110.05701\">Orthogonal Trace-Sum Maximization: Tightness of the Semidefinite Relaxation and Guarantee of Locally Optimal Solutions<\/a>. Joong-Ho Won, Teng Zhang, Hua Zhou. SIAM Journal on Optimization, 32(3):2180-2207, 2022.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2005.03238\">Phase retrieval of complex-valued objects via a randomized Kaczmarz method<\/a>. Feng Yu and Teng Zhang. Information and Inference:\u00a0 A Journal of the IMA,11(3):823-843, 2022.<\/li>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/9261996\">Design and Analysis of Secure Distributed Estimator for Vehicular Platooning in Adversarial Environment<\/a>. Raj Gautam Dutta, Yaodan Hu, Feng Yu, Teng Zhang, Yier Jin, IEEE Transactions on Intelligent Transportation Systems, 23(4):3418-3429, 2022.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1812.01255\">Phase Retrieval by Alternating Minimization with Random Initialization<\/a>. Teng Zhang, IEEE Transactions on Information Theory, 66 (7), 4563-4573, 2020.<\/li>\n<li><a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S016786552030338X\">Robust discriminant analysis using multi-directional projection pursuit<\/a>, Hsin-Hsiung Huang and Teng Zhang, Pattern Recognition Letters, Volume 138, October 2020, Pages 651-656.<\/li>\n<li><a href=\"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btz932\/31509517\/btz932.pdf\">Platform-integrated mRNA Isoform Quantification,<\/a> Jiao Sun, Jae-Woong Chang, Teng Zhang, Jeongsik Yong, Rui Kuang, and Wei Zhang, Bioinformatics, Volume 36, Issue 8, 2466\u20132473, 2020.<\/li>\n<li><a class=\"gsc_a_at\" href=\"https:\/\/arxiv.org\/abs\/1706.08167\">Phase retrieval using alternating minimization in a batch setting,<\/a> Teng Zhang, Applied and Computational Harmonic Analysis, Volume 49 (1), 279-295, 2020.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1705.01204\">Spectral clustering in the dynamic stochastic block model<\/a>,\u00a0Marianna Pensky and Teng Zhang, Electronic Journal of Statistics, Volume 13 (1), 678-709, 2019.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1706.03896\">A Well-Tempered Landscape for Non-convex Robust Subspace Recovery<\/a>,\u00a0Tyler Maunu, Teng Zhang, and Gilad Lerman, Journal of Machine Learning Research, (37):1-59, 2019.<\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1708.00257\">Robust Principal Component Analysis by Manifold Optimization<\/a>, Teng Zhang and Yi Yang, Journal of Machine Learning Research, (80):1-39, 2018. <a href=\"https:\/\/www.dropbox.com\/s\/mroqb3ywypanqq9\/code.zip?dl=0\">MATLAB Code<\/a>. <a href=\"https:\/\/1drv.ms\/u\/s!AorXkWyP3Na0g5gFOPhZOWek6X33vg\">Supplementary data.<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1709.09683\">Exact Camera Location Recovery by Least Unsquared Deviations<\/a>,\u00a0Gilad Lerman, Yunpeng Shi, Teng Zhang, SIAM Journal on Imaging Sciences, 11(4), 2692\u20132721, 2018.<\/li>\n<li><a href=\"https:\/\/journals.uwyo.edu\/index.php\/ela\/article\/view\/1879\" target=\"\" rel=\"noopener noreferrer\">A note on the non-commutative arithmetic-geometric mean inequality<\/a>, Teng Zhang, Electronic Journal of Linear Algebra, Volume 34, pp. 283-287, 2018. <a href=\"https:\/\/arxiv.org\/abs\/1411.5058\">Arxiv<\/a>\u00a0 <a href=\"https:\/\/1drv.ms\/b\/s!AorXkWyP3Na0hNYRkeZQoGXVCr5v2w?e=2hD9TI\">Errata<\/a><\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1508.05987\">Flexible Expectile Regression in Reproducing Kernel Hilbert Space<\/a>, Yi Yang, Teng Zhang and Hui Zou, Technometrics, 60(1), 26-35, 2018. <a href=\"http:\/\/cran.r-project.org\/web\/packages\/KERE\">R-package<\/a>\u00a0<img decoding=\"async\" src=\"http:\/\/cranlogs.r-pkg.org\/badges\/grand-total\/KERE\" alt=\"\" width=\"90\" align=\"middle\" \/><\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1506.02217\">Disentangling Orthogonal Matrices<\/a>, Teng Zhang and\u00a0Amit Singer, Linear Algebra and its Applications, 2017,\u00a0524, 159-181.<\/li>\n<li><a href=\"https:\/\/www.dropbox.com\/s\/vuf08zvya5y7o2h\/SIMAX_published.pdf?dl=0\">A Majorization-Minimization Algorithm for Computing the Karcher Mean of Positive Definite Matrices<\/a>, Teng Zhang, SIAM Journal on Matrix Analysis and Applications, 38-2 (2017), <span class=\"ciationPageRange\">pp. 322-342<\/span>. (<a href=\"https:\/\/drive.google.com\/open?id=0B5JGyCcwhc50NEQwY3dCcWlMVEE\">Matlab code<\/a>)<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1301.2007\">Spectral Clustering Based on Local PCA<\/a>, Ery Arias-Castro, Gilad Lerman, and Teng Zhang. (<a href=\"https:\/\/1drv.ms\/u\/s!AorXkWyP3Na0vDulWa0OEte5V9MW?e=6RaHr1\">Matlab code<\/a>), Journal of Machine Learning Research, 2017, 18 (9), 1-57.<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1602.06632\">Denoising and Covariance Estimation of Single Particle Cryo-EM Images.\u00a0<\/a>Tejal Bhamre, Teng Zhang\u00a0and\u00a0Amit Singer, <span dir=\"ltr\">Journal of Structural Biology,\u00a0Volume 195, Issue 1, July 2016, Pages 72\u201381<\/span>.<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1401.3424\">Marchenko-Pastur Law for Tyler&#8217;s M-estimator<\/a>, Teng Zhang, Xiuyuan Cheng and Amit Singer, Journal of Multivariate Analysis,\u00a0Volume 149, July 2016, 114\u2013123.<\/li>\n<li><a href=\"http:\/\/imaiai.oxfordjournals.org\/content\/early\/2015\/11\/12\/imaiai.iav012.abstract\">Robust subspace recovery by Tyler&#8217;s M-estimator,<\/a> Teng Zhang, Information and Inference:\u00a0 A Journal of the IMA, 2016, 5 (1): 1-21. <a href=\"https:\/\/arxiv.org\/abs\/1206.1386\">With proof of Theorem 1.1 corrected.<\/a><\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1202.4044\">Robust computation of linear models by convex relaxation<\/a>, Gilad Lerman, Michael McCoy, Joel A. Tropp, and Teng Zhang. Foundation of Computational Mathematics. 2015 15 (2): 363-410. <span style=\"line-height: 17.06px\">(<\/span><a style=\"line-height: 17.06px\" href=\"https:\/\/drive.google.com\/open?id=0B5JGyCcwhc50b3JrdTNRLWFKcEE\">Matlab code<\/a><span style=\"line-height: 17.06px\">)<\/span><\/li>\n<li><a href=\"http:\/\/users.stat.umn.edu\/~zouxx019\/Papers\/precisionmatrix.pdf\">Sparse Precision Matrix Estimation via Positive Definite Constrained Minimization of $\\ell_1$ Penalized D-Trace Loss<\/a>. Teng Zhang and Hui Zou. Biometrika, 2014, 101 (1): 103-120. <span style=\"line-height: 17.06px\">(<\/span><a style=\"line-height: 17.06px\" href=\"https:\/\/1drv.ms\/u\/s!AorXkWyP3Na0gaJBxSwFJIXObXZHVw?e=wnkEbx\">Matlab code<\/a><span style=\"line-height: 17.06px\">)<\/span><\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1012.4116\">lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers<\/a>, Gilad Lerman and Teng Zhang. Constructive Approximation, 2014, 40:329\u2013385.<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1112.4863\">A Novel M-Estimator for Robust PCA<\/a>, Teng Zhang and Gilad Lerman. Journal of Machine Learning Research, 2014, 15(1): 749-808. (<a href=\"https:\/\/drive.google.com\/open?id=0B5JGyCcwhc50b0ktbmZOWUxCRjA\">Matlab code<\/a>)<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1304.3206\">Multivariate Generalized Gaussian Distribution: Convexity and Graphical Models<\/a>, Teng Zhang, Ami Wiesel, Maria Sabrina Grec. IEEE Transactions on Signal Processing, 2013, Vol. 61, Issue. 16, 4141-4148.<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1010.3460\">Hybrid Linear Modeling via Local Best Fit Flats<\/a>, Teng Zhang, Arthur Szlam, Yi Wang and Gilad Lerman. International Journal of Computer Vision, 2012, Vol. 100, Issue.3, 217-240 (<a href=\"https:\/\/sciencescosmaincms.cm.ucf.edu\/math\/tengz\/lbf\">Matlab code and supplementary material<\/a>)<\/li>\n<li><a href=\"http:\/\/arxiv.org\/abs\/1104.3770\">Robust recovery of multiple subspaces by geometric lp minimization<\/a>, Gilad Lerman and Teng Zhang, Annals of Statistics 2011, Vol. 39, No. 5, 2686-2715.<\/li>\n<\/ul>\n<div dir=\"ltr\"><b><span style=\"font-size: medium\">Conference papers:<\/span><\/b><\/div>\n<div dir=\"ltr\"><\/div>\n<ul>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2404.11590\">A Subspace-Constrained Tyler&#8217;s Estimator and its Applications to Structure from Motion<\/a>. Feng Yu, Teng Zhang, Gilad Lerman, CVPR 2024.<\/li>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/9283595\">Resilient Distributed Estimator with Information Consensus for CPS Security<\/a>. Feng Yu, Yaodan Hu, Teng Zhang, Yier Jin, IEEE 38th International Conference on Computer Design (ICCD), 2020.<\/li>\n<li><a href=\"https:\/\/www.ndss-symposium.org\/ndss-paper\/cloudleak-large-scale-deep-learning-models-stealing-through-adversarial-examples\/\">CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples<\/a>, Honggang Yu, Kaichen Yang, Teng Zhang, Yun-Yun Tsai, Tsung-Yi Ho, Yier Jin, Network and Distributed System Security Symposium (NDSS) 2020.<\/li>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/document\/8815298\">Resilient Distributed Filter for State Estimation of Cyber-Physical Systems Under Attack<\/a>, Raj Gautam Dutta, Gainesville, Teng Zhang, Yier Jin, American Control Conference (ACC)\u00a02019.<\/li>\n<li><a href=\"https:\/\/ieeexplore.ieee.org\/document\/8587713\">Security for Safety: A Path Toward Building Trusted Autonomous Vehicles<\/a>, Raj Gautam Dutta, Feng Yu, Teng Zhang, Yaodan Hu, Yier Jin, IEEE\/ACM International Conference on Computer-Aided Design (ICCAD), 2018.<\/li>\n<li><a href=\"http:\/\/jin.ece.ufl.edu\/papers\/DAC17.pdf\">Estimation of Safe States of Autonomous System Under\u00a0Attack<\/a>, Raj Gautam Dutta, Xiaolong Guo, Teng Zhang, Kevin Kwiat, Charles Kamhoua, Laurent Njilla and Yier Jin. The 54th Design Automation Conference, 2017.<\/li>\n<li><a href=\"https:\/\/sciencescosmaincms.cm.ucf.edu\/math\/tengz\/wp-content\/uploads\/sites\/4\/2016\/08\/automatic-diagonal-loading-3.pdf\">Automatic diagonal loading for Tyler&#8217;s robust covariance estimator,<\/a> Teng Zhang and Ami Wiesel,\u00a02016 IEEE Workshop on Statistical Signal Processing (SSP 2016).<\/li>\n<li>\n<div><a href=\"http:\/\/arxiv.org\/abs\/1412.0494\">Orthogonal Matrix Retrieval in Cryo-Electron Microscopy<\/a>, <span style=\"line-height: 23.27px\">Tejal Bhamre, Teng Zhang and Amit Singer. 2015 IEEE International Symposium on Biomedical Imaging.<\/span><\/div>\n<\/li>\n<li>\n<div><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v33\/goes14.pdf\">Robust Stochastic Principal Component Analysis<\/a>, John Goes, Teng Zhang, Raman Arora and Gilad Lerman. Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS 2014).<\/div>\n<\/li>\n<li>\n<div><a href=\"http:\/\/arxiv.org\/PS_cache\/arxiv\/pdf\/1005\/1005.0858v1.pdf\">Randomized Hybrid Linear Modeling by Local Best-fit Flats<\/a>, Teng Zhang, Arthur Szlam, Yi Wang and Gilad Lerman. Proceedings of the 2010 IEEE 23rd International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1927-1934. (<a href=\"https:\/\/sciencescosmaincms.cm.ucf.edu\/math\/tengz\/lbf\">Matlab code and supplementary material<\/a>)<\/div>\n<\/li>\n<li>\n<div><a href=\"http:\/\/arxiv.org\/abs\/0909.3123\">Median K-Flats for Hybrid Linear Modeling with Many Outliers,<\/a> Teng Zhang, Arthur Szlam and Gilad Lerman. Proc. of 2nd IEEE International Workshop on Subspace Methods (Subspace 2009), pp. 234-241 (2009). (<a href=\"https:\/\/drive.google.com\/open?id=0B5JGyCcwhc50QWl5ZkpiOG9xaEU\">Matlab code<\/a>)<\/div>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Associate Professor, Department of Mathematics Email: Teng.Zhang@ucf.edu Office: MSB building 202G Google scholar Publications: Monograph: Structured Robust Covariance Estimation, Ami Wiesel and Teng Zhang, Foundations and Trends in Signal Processing: Vol. 8: No. 3, pp 127-216, 2015. Manuscripts: Theoretical Guarantees for the Subspace-Constrained Tyler&#8217;s Estimator. Gilad Lerman, Feng Yu, and Teng Zhang. Projected Gradient Descent [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-9","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/pages\/9","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/comments?post=9"}],"version-history":[{"count":27,"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/pages\/9\/revisions"}],"predecessor-version":[{"id":335,"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/pages\/9\/revisions\/335"}],"wp:attachment":[{"href":"https:\/\/sciences.ucf.edu\/math\/tengz\/wp-json\/wp\/v2\/media?parent=9"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}