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Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary Learning

Jun 30, 2020
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

* 36 pages 

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The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R

Jun 27, 2020
Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu

* Journal of Machine Learning Research 16 (2015) 553-557 

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Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python

Jun 27, 2020
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

* Journal of Machine Learning Research 20 (2019): 44-1 

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Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality

Feb 24, 2020
Yi Zhang, Orestis Plevrakis, Simon S. Du, Xingguo Li, Zhao Song, Sanjeev Arora


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On Computation and Generalization of Generative Adversarial Imitation Learning

Jan 12, 2020
Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao


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On Recoverability of Randomly Compressed Tensors with Low CP Rank

Jan 08, 2020
Shahana Ibrahim, Xiao Fu, Xingguo Li

* 13 pages, 1 figure 

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On Generalization Bounds of a Family of Recurrent Neural Networks

Nov 04, 2019
Minshuo Chen, Xingguo Li, Tuo Zhao

* 30 pages, 5 figures 

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ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization

Oct 16, 2019
Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David Cox


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NOODL: Provable Online Dictionary Learning and Sparse Coding

Mar 15, 2019
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

* Published as a conference paper at the International Conference on Learning Representations (ICLR) 2019; 42 Pages with appendix 

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Target-based Hyperspectral Demixing via Generalized Robust PCA

Feb 26, 2019
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

* 2017 51st Asilomar Conference on Signals, Systems, and Computers 
* 5 Pages; Index Terms - Hyperspectral imaging, Robust-PCA, Dictionary Sparse, Matrix Demixing, Target Localization, and Remote Sensing. arXiv admin note: substantial text overlap with arXiv:1902.10238 

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A Dictionary-Based Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing

Feb 26, 2019
Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis Haupt

* 13 pages; Index Terms - Hyperspectral imaging, Robust-PCA, Dictionary Sparse, Matrix Demixing, Target Localization, and Remote Sensing 

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A Dictionary-Based Generalization of Robust PCA Part I: Study of Theoretical Properties

Feb 21, 2019
Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis Haupt

* 13 Pages; Index terms - Low-rank, Matrix Demixing, Dictionary Sparse, Target Localization, and Robust PCA 

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A Dictionary Based Generalization of Robust PCA

Feb 21, 2019
Sirisha Rambhatla, Xingguo Li, Jarvis Haupt

* 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP) 
* 5 pages; Index terms -- Low-rank, Dictionary sparse, Matrix Demixing, and Generalized Robust PCA 

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On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization

Oct 02, 2018
Zhehui Chen, Xingguo Li, Lin F. Yang, Jarvis Haupt, Tuo Zhao

* 29 pages, 2 figures 

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On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond

Oct 02, 2018
Xingguo Li, Junwei Lu, Zhaoran Wang, Jarvis Haupt, Tuo Zhao


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Towards Black-box Iterative Machine Teaching

Jun 05, 2018
Weiyang Liu, Bo Dai, Xingguo Li, Zhen Liu, James M. Rehg, Le Song

* Published in ICML 2018 

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On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions

Feb 15, 2018
Xingguo Li, Lin F. Yang, Jason Ge, Jarvis Haupt, Tong Zhang, Tuo Zhao

* 36 pages, 5 figures, 1 table, Accepted at NIPS 2017 

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On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About Its Nonsmooth Loss Function

Feb 14, 2018
Xingguo Li, Haoming Jiang, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao


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Deep Hyperspherical Learning

Jan 30, 2018
Weiyang Liu, Yan-Ming Zhang, Xingguo Li, Zhiding Yu, Bo Dai, Tuo Zhao, Le Song

* NIPS 2017 (Spotlight) 

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Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization

Jan 20, 2018
Xingguo Li, Junwei Lu, Raman Arora, Jarvis Haupt, Han Liu, Zhaoran Wang, Tuo Zhao


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Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction

Dec 23, 2017
Xingguo Li, Raman Arora, Han Liu, Jarvis Haupt, Tuo Zhao


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On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization

Nov 22, 2017
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong

* Accepted by JLMR 

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Near Optimal Sketching of Low-Rank Tensor Regression

Sep 20, 2017
Jarvis Haupt, Xingguo Li, David P. Woodruff

* 36 pages, 2 figures, 2 tables, Accepted at NIPS 2017 

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Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices

Dec 07, 2016
Xingguo Li, Jarvis Haupt

* 16 pages, 4 figures 

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Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling

Nov 19, 2014
Xingguo Li, Jarvis Haupt

* 16 pages, 7 figures, 2 tables, IEEE Transactions on Signal Processing (submitted) 

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