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Tensor completion is a natural higher-order generalization of matrix completion where the goal is to recover a low-rank tensor from sparse observations of its entries.
Introductory lectures on convex programming volume i: Basic course
Yurii Nesterov · 1998
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Matrix rank minimization with applications [ph. d. thesis]
Maryam Fazel · 2002
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Classical deterministic complexity of edmonds’ problem and quantum entanglement
Leonid Gurvits · 2003
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Identifiability of parameters in latent structure models with many observed variables
Elizabeth S Allman, Catherine Matias, John A Rhodes, et al · 2009
Earlier work this paper cites.
Exact matrix completion via convex optimization
Emmanuel J Candès and Benjamin Recht · 2009
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Tensor completion and low-n-rank tensor recovery via convex optimization
Silvia Gandy, Benjamin Recht, and Isao Yamada · 2011
Earlier work this paper cites.
The convex geometry of linear inverse problems
Venkat Chandrasekaran, Benjamin Recht, Pablo A Parrilo, and Alan S Willsky · 2012
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Geometric algorithms and combinatorial optimization
Martin Grötschel, László Lovász, and Alexander Schrijver · 2012
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Tensor completion for estimating missing values in visual data
Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye · 2012
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More data speeds up training time in learning halfspaces over sparse vectors
Amit Daniely, Nati Linial, and Shai Shalev-Shwartz · 2013
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Most tensor problems are np-hard
Christopher J Hillar and Lek-Heng Lim · 2013
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Low-rank matrix completion using alternating minimization
Prateek Jain, Praneeth Netrapalli, and Sujay Sanghavi · 2013
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Tensor completion based on nuclear norm minimization for 5d seismic data reconstruction
Nadia Kreimer, Aaron Stanton, and Mauricio D Sacchi · 2013
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Interpolation using hankel tensor completion
Stewart Trickett, Lynn Burroughs, Andrew Milton, et al · 2013
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Tensor decompositions for learning latent variable models
Animashree Anandkumar, Rong Ge, Daniel Hsu, Sham M Kakade, and Matus Telgarsky · 2014
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Smoothed analysis of tensor decompositions
Aditya Bhaskara, Moses Charikar, Ankur Moitra, and Aravindan Vijayaraghavan · 2014
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Understanding alternating minimization for matrix completion
Moritz Hardt · 2014
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Accurate recovery of internet traffic data: A tensor completion approach
Kun Xie, Lele Wang, Xin Wang, Gaogang Xie, Jigang Wen, and Guangxing Zhang · 2016
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On tensor completion via nuclear norm minimization
Ming Yuan and Cun-Hui Zhang · 2016
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Efficient tensor completion for color image and video recovery: Low-rank tensor train
Johann A Bengua, Ho N Phien, Hoang Duong Tuan, and Minh N Do · 2017
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Low-rank tensor completion with total variation for visual data inpainting
Xutao Li, Yunming Ye, and Xiaofei Xu · 2017
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An adaptive weighted tensor completion method for the recovery of remote sensing images with missing data
Michael Kwok-Po Ng, Qiangqiang Yuan, Li Yan, and Jing Sun · 2017
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Prateek Jain and Sewoong Oh · 2014
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An introduction to matrix concentration inequalities
Joel A Tropp · 2015
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Rubik: Knowledge guided tensor factorization and completion for health data analytics
Yichen Wang, Robert Chen, Joydeep Ghosh, Joshua C Denny, Abel Kho, You Chen, Bradley A Malin, and Jimeng Sun · 2015
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Noisy tensor completion via the sum-of-squares hierarchy
Boaz Barak and Ankur Moitra · 2016
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Short-term traffic prediction based on dynamic tensor completion
Huachun Tan, Yuankai Wu, Bin Shen, Peter J Jin, and Bin Ran · 2016
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Aaron Potechin and David Steurer · 2017
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Algorithmic aspects of machine learning
Ankur Moitra · 2018
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Spectral algorithms for tensor completion
Andrea Montanari and Nike Sun · 2018
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Fairness-aware tensor-based recommendation
Ziwei Zhu, Xia Hu, and James Caverlee · 2018
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Nonconvex low-rank tensor completion from noisy data
Changxiao Cai, Gen Li, H Vincent Poor, and Yuxin Chen · 2019
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On polynomial time methods for exact low-rank tensor completion
Dong Xia and Ming Yuan · 2019
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