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Ming Yuan

Georgia Institute of Technology

Assessing Fairness in Classification Parity of Machine Learning Models in Healthcare


Feb 07, 2021
Ming Yuan, Vikas Kumar, Muhammad Aurangzeb Ahmad, Ankur Teredesai


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A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration


Aug 06, 2020
Yuetian Luo, Garvesh Raskutti, Ming Yuan, Anru R. Zhang


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Perturbation Bounds for Orthogonally Decomposable Tensors and Their Applications in High Dimensional Data Analysis


Jul 17, 2020
Arnab Auddy, Ming Yuan


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ISLET: Fast and Optimal Low-rank Tensor Regression via Importance Sketching


Nov 09, 2019
Anru Zhang, Yuetian Luo, Garvesh Raskutti, Ming Yuan


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On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives


Sep 07, 2019
Tong Li, Ming Yuan


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Statistical Inferences of Linear Forms for Noisy Matrix Completion


Aug 31, 2019
Dong Xia, Ming Yuan


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Statistically Optimal and Computationally Efficient Low Rank Tensor Completion from Noisy Entries


Mar 19, 2018
Dong Xia, Ming Yuan, Cun-Hui Zhang


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Joint Demosaicing and Denoising with Perceptual Optimization on a Generative Adversarial Network


Feb 13, 2018
Weishong Dong, Ming Yuan, Xin Li, Guangming Shi


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Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective


Nov 20, 2017
Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh


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Effective Tensor Sketching via Sparsification


Nov 16, 2017
Dong Xia, Ming Yuan


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On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests


Sep 24, 2017
Krishnakumar Balasubramanian, Tong Li, Ming Yuan


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On Polynomial Time Methods for Exact Low Rank Tensor Completion


Feb 22, 2017
Dong Xia, Ming Yuan

* 56 pages, 4 figures 

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Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression


Nov 30, 2016
Han Chen, Garvesh Raskutti, Ming Yuan

* 42 pages, 6 figures 

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Incoherent Tensor Norms and Their Applications in Higher Order Tensor Completion


Jun 10, 2016
Ming Yuan, Cun-Hui Zhang


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Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition


Mar 10, 2015
Ming Yuan, Ding-Xuan Zhou


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Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation


Sep 17, 2014
Luwan Zhang, Grace Wahba, Ming Yuan


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Rate-Optimal Detection of Very Short Signal Segments


Jul 10, 2014
T. Tony Cai, Ming Yuan


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On Tensor Completion via Nuclear Norm Minimization


May 07, 2014
Ming Yuan, Cun-Hui Zhang


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Discussion: Latent variable graphical model selection via convex optimization


Nov 05, 2012
Ming Yuan

* Annals of Statistics 2012, Vol. 40, No. 4, 1968-1972 
* Published in at http://dx.doi.org/10.1214/12-AOS979 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

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High Dimensional Semiparametric Gaussian Copula Graphical Models


Jul 27, 2012
Han Liu, Fang Han, Ming Yuan, John Lafferty, Larry Wasserman

* 34 pages, 10 figures; the Annals of Statistics, 2012 

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The Nonparanormal SKEPTIC


Jun 27, 2012
Han Liu, Fang Han, Ming Yuan, John Lafferty, Larry Wasserman

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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Structured variable selection in support vector machines


Feb 22, 2008
Seongho Wu, Hui Zou, Ming Yuan

* Electronic Journal of Statistics 2008, Vol. 2, 103-117 
* Published in at http://dx.doi.org/10.1214/07-EJS125 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

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