Assistant Professor, Department of Mathematics
Office: MSB building 202G
- Structured Robust Covariance Estimation, Ami Wiesel and Teng Zhang, Foundations and Trends in Signal Processing: Vol. 8: No. 3, pp 127-216, 2015.
- Phase retrieval of complex-valued objects via a randomized Kaczmarz method.
- Tightness of the semidefinite relaxation for orthogonal trace-sum maximization.
- An Algorithm for Graph-Fused Lasso Based on Graph Decomposition. Feng Yu, Yi Yang, and Teng Zhang.
- Element-wise estimation error of a total variation regularized estimator for change point detection.
- Anisotropic twicing for single particle reconstruction using autocorrelation analysis. Tejal Bhamre, Teng Zhang, and Amit Singer.
- Phase Retrieval by Alternating Minimization with Random Initialization. Teng Zhang, accepted to IEEE Transactions on Information Theory.
- Platform-integrated mRNA Isoform Quantification, Jiao Sun, Jae-Woong Chang, Teng Zhang, Jeongsik Yong, Rui Kuang, and Wei Zhang, Bioinformatics, Volume 36, Issue 8, 2466–2473, 15 April 2020.
- Phase retrieval using alternating minimization in a batch setting, Teng Zhang, Applied and Computational Harmonic Analysis, Volume 49 (1), 279-295, 2020.
- Spectral clustering in the dynamic stochastic block model, Marianna Pensky and Teng Zhang, Electronic Journal of Statistics, Volume 13 (1), 678-709, 2019.
- A Well-Tempered Landscape for Non-convex Robust Subspace Recovery, Tyler Maunu, Teng Zhang, and Gilad Lerman, Journal of Machine Learning Research, (37):1-59, 2019.
- Robust Principal Component Analysis by Manifold Optimization, Teng Zhang and Yi Yang, Journal of Machine Learning Research, (80):1-39, 2018. MATLAB Code. Supplementary data.
- Exact Camera Location Recovery by Least Unsquared Deviations, Gilad Lerman, Yunpeng Shi, Teng Zhang, SIAM Journal on Imaging Sciences, 11(4), 2692–2721, 2018.
- A note on the non-commutative arithmetic-geometric mean inequality, Teng Zhang, Electronic Journal of Linear Algebra, Volume 34, pp. 283-287, 2018.
- Flexible Expectile Regression in Reproducing Kernel Hilbert Space, Yi Yang, Teng Zhang and Hui Zou, Technometrics, 60(1), 26-35, 2018. R-package
- Disentangling Orthogonal Matrices, Teng Zhang and Amit Singer, Linear Algebra and its Applications, 2017, 524, 159-181.
- A Majorization-Minimization Algorithm for Computing the Karcher Mean of Positive Definite Matrices, Teng Zhang, SIAM Journal on Matrix Analysis and Applications, 38-2 (2017), pp. 322-342. (Matlab code)
- Spectral Clustering Based on Local PCA, Ery Arias-Castro, Gilad Lerman, and Teng Zhang. (Matlab code), Journal of Machine Learning Research, 2017, 18 (9), 1-57.
- Denoising and Covariance Estimation of Single Particle Cryo-EM Images. Tejal Bhamre, Teng Zhang and Amit Singer, Journal of Structural Biology, Volume 195, Issue 1, July 2016, Pages 72–81.
- Marchenko-Pastur Law for Tyler’s M-estimator, Teng Zhang, Xiuyuan Cheng and Amit Singer, Journal of Multivariate Analysis, Volume 149, July 2016, 114–123.
- Robust subspace recovery by Tyler’s M-estimator, Teng Zhang, Information and Inference: A Journal of the IMA, 2016, 5 (1): 1-21.
- Robust computation of linear models by convex relaxation, Gilad Lerman, Michael McCoy, Joel A. Tropp, and Teng Zhang. Foundation of Computational Mathematics. 2015 15 (2): 363-410. (Matlab code)
- Sparse Precision Matrix Estimation via Positive Definite Constrained Minimization of $\ell_1$ Penalized D-Trace Loss. Teng Zhang and Hui Zou. Biometrika, 2014, 101 (1): 103-120. (Matlab code)
- lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers, Gilad Lerman and Teng Zhang. Constructive Approximation, 2014, 40:329–385.
- A Novel M-Estimator for Robust PCA, Teng Zhang and Gilad Lerman. Journal of Machine Learning Research, 2014, 15(1): 749-808. (Matlab code)
- Multivariate Generalized Gaussian Distribution: Convexity and Graphical Models, Teng Zhang, Ami Wiesel, Maria Sabrina Grec. IEEE Transactions on Signal Processing, 2013, Vol. 61, Issue. 16, 4141-4148.
- Hybrid Linear Modeling via Local Best Fit Flats, Teng Zhang, Arthur Szlam, Yi Wang and Gilad Lerman. International Journal of Computer Vision, 2012, Vol. 100, Issue.3, 217-240 (Matlab code and supplementary material)
- Robust recovery of multiple subspaces by geometric lp minimization, Gilad Lerman and Teng Zhang, Annals of Statistics 2011, Vol. 39, No. 5, 2686-2715.
- CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples, Honggang Yu, Kaichen Yang, Teng Zhang, Yun-Yun Tsai, Tsung-Yi Ho, Yier Jin, Network and Distributed System Security Symposium (NDSS) 2020.
- Resilient Distributed Filter for State Estimation of Cyber-Physical Systems Under Attack, Raj Gautam Dutta, Gainesville, Teng Zhang, Yier Jin, American Control Conference (ACC)
- Security for Safety: A Path Toward Building Trusted Autonomous Vehicles, Raj Gautam Dutta, Feng Yu, Teng Zhang, Yaodan Hu, Yier Jin, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2018.
- Estimation of Safe States of Autonomous System Under Attack, Raj Gautam Dutta, Xiaolong Guo, Teng Zhang, Kevin Kwiat, Charles Kamhoua, Laurent Njilla and Yier Jin. The 54th Design Automation Conference, 2017.
- Automatic diagonal loading for Tyler’s robust covariance estimator, Teng Zhang and Ami Wiesel, 2016 IEEE Workshop on Statistical Signal Processing (SSP 2016).
Orthogonal Matrix Retrieval in Cryo-Electron Microscopy, Tejal Bhamre, Teng Zhang and Amit Singer. 2015 IEEE International Symposium on Biomedical Imaging.
Robust Stochastic Principal Component Analysis, John Goes, Teng Zhang, Raman Arora and Gilad Lerman. Seventeenth International Conference on Artificial Intelligence and Statistics (AISTATS 2014).
Randomized Hybrid Linear Modeling by Local Best-fit Flats, 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. (Matlab code and supplementary material)
Median K-Flats for Hybrid Linear Modeling with Many Outliers, Teng Zhang, Arthur Szlam and Gilad Lerman. Proc. of 2nd IEEE International Workshop on Subspace Methods (Subspace 2009), pp. 234-241 (2009). (Matlab code)
I have opportunities for undergraduate and graduate students to assist with various research projects. If you are interested, please contact me to learn about specific research and training opportunities.