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2001.05484
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Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data
Annals of Statistics (Ann. Stat.), 2020
15 January 2020
Yuxin Chen
Jianqing Fan
Cong Ma
Yuling Yan
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Papers citing
"Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data"
32 / 32 papers shown
RGNMR: A Gauss-Newton method for robust matrix completion with theoretical guarantees
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Alternating minimization for square root principal component pursuit
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Xudong Li
Yangjing Zhang
451
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31 Dec 2024
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\ell_0
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factor analysis
Linyang Wang
Wanquan Liu
Bin Zhu
397
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13 Nov 2024
Exact Recovery Guarantees for Parameterized Nonlinear System Identification Problem under Sparse Disturbances or Semi-Oblivious Attacks
Haixiang Zhang
Baturalp Yalcin
Javad Lavaei
Eduardo Sontag
AAML
522
1
0
30 Aug 2024
Leave-One-Out Analysis for Nonconvex Robust Matrix Completion with General Thresholding Functions
Tianming Wang
Ke Wei
331
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28 Jul 2024
Heterogeneous Treatment Effects in Panel Data
R. Levi
Elisabeth Paulson
Georgia Perakis
Emily Zhang
CML
229
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09 Jun 2024
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization
Cong Ma
Xingyu Xu
Tian Tong
Yuejie Chi
416
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09 Oct 2023
Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Jialun Zhang
Hong-Ming Chiu
Richard Y. Zhang
429
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0
26 May 2023
Exact Recovery for System Identification with More Corrupt Data than Clean Data
Baturalp Yalcin
Haixiang Zhang
Javad Lavaei
Murat Arcak
452
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17 May 2023
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
Annals of Statistics (Ann. Stat.), 2023
Yuchen Zhou
Yuxin Chen
373
11
0
10 Mar 2023
Optimal tuning-free convex relaxation for noisy matrix completion
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Yuepeng Yang
Cong Ma
398
8
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12 Jul 2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent
Information and Inference A Journal of the IMA (JIII), 2022
Harry Dong
Tian Tong
Cong Ma
Yuejie Chi
319
19
0
18 Jun 2022
Robust Matrix Completion with Heavy-tailed Noise
Journal of the American Statistical Association (JASA), 2022
Bingyan Wang
Jianqing Fan
281
15
0
09 Jun 2022
Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption
Journal of machine learning research (JMLR), 2022
Lihu Xu
Fang Yao
Qiuran Yao
Huiming Zhang
346
17
0
10 Jan 2022
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery
Neural Information Processing Systems (NeurIPS), 2021
Lijun Ding
Liwei Jiang
Yudong Chen
Qing Qu
Zhihui Zhu
271
30
0
23 Sep 2021
Inference for Heteroskedastic PCA with Missing Data
Annals of Statistics (Ann. Stat.), 2021
Yuling Yan
Yuxin Chen
Jianqing Fan
418
30
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26 Jul 2021
GNMR: A provable one-line algorithm for low rank matrix recovery
Pini Zilber
B. Nadler
702
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24 Jun 2021
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery
Junhui Zhang
Jingkai Yan
John N. Wright
291
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0
17 Jun 2021
Learning Treatment Effects in Panels with General Intervention Patterns
Neural Information Processing Systems (NeurIPS), 2021
Vivek F. Farias
Andrew A. Li
Tianyi Peng
CML
224
10
0
05 Jun 2021
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model
Neural Information Processing Systems (NeurIPS), 2021
Bingyan Wang
Yuling Yan
Jianqing Fan
509
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0
28 May 2021
Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization
Journal of the American Statistical Association (JASA), 2021
Jian-Feng Cai
Jingyang Li
Dong Xia
649
35
0
16 Mar 2021
Matrix optimization based Euclidean embedding with outliers
Computational optimization and applications (Comput. Optim. Appl.), 2020
Qian Zhang
Xinyuan Zhao
Chao Ding
351
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23 Dec 2020
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
696
217
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15 Dec 2020
Outlier-robust sparse/low-rank least-squares regression and robust matrix completion
Philip Thompson
503
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12 Dec 2020
Learning Mixtures of Low-Rank Models
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Yanxi Chen
Cong Ma
H. Vincent Poor
Yuxin Chen
371
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23 Sep 2020
Recent Developments on Factor Models and its Applications in Econometric Learning
Annual Review of Financial Economics (ARFE), 2020
Jianqing Fan
Kunpeng Li
Yuan Liao
295
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21 Sep 2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs
Yuxin Chen
Jianqing Fan
B. Wang
Yuling Yan
457
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0
04 Aug 2020
Fixing Inventory Inaccuracies At Scale
Manufacturing & Service Operations Management (MSOM), 2020
Vivek F. Farias
Andrew A. Li
Tianyi Peng
248
5
0
23 Jun 2020
Median Matrix Completion: from Embarrassment to Optimality
Weidong Liu
Xiaojun Mao
Raymond K. W. Wong
304
3
0
18 Jun 2020
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai
H. Vincent Poor
Yuxin Chen
351
26
0
15 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
Tian Tong
Cong Ma
Yuejie Chi
601
142
0
18 May 2020
Nonconvex Matrix Factorization from Rank-One Measurements
Yuanxin Li
Cong Ma
Yuxin Chen
Yuejie Chi
219
57
0
17 Feb 2018
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