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Singular vectors under random perturbation
12 April 2010
V. Vu
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Papers citing
"Singular vectors under random perturbation"
26 / 26 papers shown
Matrix perturbation bounds via contour bootstrapping
Phuc Tran
Van Vu
279
0
0
07 Jul 2024
A Universal Metric of Dataset Similarity for Cross-silo Federated Learning
Ahmed Elhussein
Gamze Gürsoy
FedML
OOD
370
4
0
29 Apr 2024
Uniform error bound for PCA matrix denoising
Bernoulli (Bernoulli), 2023
Xin T. Tong
Wanjie Wang
Yuguan Wang
274
7
0
22 Jun 2023
Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Danushka Bollegala
SSL
264
8
0
26 Apr 2022
Multivariate Analysis for Multiple Network Data via Semi-Symmetric Tensor PCA
Michael Weylandt
George Michailidis
359
1
0
09 Feb 2022
Power Iteration for Tensor PCA
Journal of machine learning research (JMLR), 2020
Jiaoyang Huang
Daniel Zhengyu Huang
Qing Yang
Guang Cheng
298
21
0
26 Dec 2020
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration
Yuetian Luo
Garvesh Raskutti
M. Yuan
Anru R. Zhang
367
14
0
06 Aug 2020
Learning with Semi-Definite Programming: new statistical bounds based on fixed point analysis and excess risk curvature
Journal of machine learning research (JMLR), 2020
Stéphane Chrétien
Mihai Cucuringu
Guillaume Lecué
Lucie Neirac
237
5
0
04 Apr 2020
On the perturbation series for eigenvalues and eigenprojections
Martin Wahl
201
11
0
18 Oct 2019
Subspace Estimation from Unbalanced and Incomplete Data Matrices:
ℓ
2
,
∞
\ell_{2,\infty}
ℓ
2
,
∞
Statistical Guarantees
Changxiao Cai
Gen Li
Yuejie Chi
H. Vincent Poor
Yuxin Chen
498
13
0
09 Oct 2019
Achieving the Bayes Error Rate in Synchronization and Block Models by SDP, Robustly
Yingjie Fei
Yudong Chen
434
24
0
21 Apr 2019
On the Dimensionality of Word Embedding
Zi Yin
Yuanyuan Shen
221
214
0
11 Dec 2018
Asymmetry Helps: Eigenvalue and Eigenvector Analyses of Asymmetrically Perturbed Low-Rank Matrices
Yuxin Chen
Chen Cheng
Jianqing Fan
446
42
0
30 Nov 2018
Matrices with Gaussian noise: optimal estimates for singular subspace perturbation
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2018
Sean O’Rourke
Van Vu
Ke Wang
414
13
0
02 Mar 2018
Understand Functionality and Dimensionality of Vector Embeddings: the Distributional Hypothesis, the Pairwise Inner Product Loss and Its Bias-Variance Trade-off
Zi Yin
270
8
0
01 Mar 2018
Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach
Ming Yu
Varun Gupta
Mladen Kolar
317
24
0
20 Feb 2018
Unperturbed: spectral analysis beyond Davis-Kahan
Justin Eldridge
M. Belkin
Yusu Wang
230
102
0
20 Jun 2017
A Non-generative Framework and Convex Relaxations for Unsupervised Learning
Neural Information Processing Systems (NeurIPS), 2016
Elad Hazan
Tengyu Ma
333
18
0
04 Oct 2016
A Semi-Definite Programming approach to low dimensional embedding for unsupervised clustering
Stéphane Chrétien
Clément Dombry
A. Faivre
234
10
0
29 Jun 2016
Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Statistics
T. Tony Cai
Anru R. Zhang
422
176
0
02 May 2016
Recovering Structured Probability Matrices
Qingqing Huang
Sham Kakade
Weihao Kong
Gregory Valiant
648
12
0
21 Feb 2016
Community detection in sparse networks via Grothendieck's inequality
Probability theory and related fields (PTRF), 2014
O. Guédon
Roman Vershynin
505
215
0
17 Nov 2014
Random perturbation of low rank matrices: Improving classical bounds
Sean O’Rourke
V. Vu
Ke Wang
784
115
0
12 Nov 2013
Singular Vector Perturbation under Gaussian Noise
SIAM Journal on Matrix Analysis and Applications (SIMAX), 2012
Rongrong Wang
270
34
0
09 Aug 2012
Tangent space estimation for smooth embeddings of Riemannian manifolds
Hemant Tyagi
Elif Vural
P. Frossard
257
65
0
05 Aug 2012
Spectral clustering and the high-dimensional stochastic blockmodel
Karl Rohe
S. Chatterjee
Bin Yu
747
984
0
09 Jul 2010
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