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The problem of completing a large matrix with lots of missing entries has received widespread attention in the last couple of decades.
The geometry of graphs and some of its algorithmic applications
Nathan Linial, Eran London, and Yuri Rabinovich · 1995
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Learning collaborative information filters
Daniel Billsus and Michael J. Pazzani · 1998
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Spectral analysis of data
Yossi Azar, Amos Fiat, Anna Karlin, Frank McSherry, and Jared Saia · 2001
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Eigentaste: A constant time collaborative filtering algorithm
Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins · 2001
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Fast maximum margin matrix factorization for collaborative prediction
Jasson D. M. Rennie and Nathan Srebro · 2005
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Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
Emmanuel J. Candès, Justin Romberg, and Terence Tao · 2006
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Compressed sensing
David L. Donoho · 2006
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Unsupervised learning of image manifolds by semidefinite programming
Kilian Q. Weinberger and Lawrence K. Saul · 2006
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Fast computation of low-rank matrix approximations
Dimitris Achlioptas and Frank McSherry · 2007
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Convex multi-task feature learning
Andreas Argyriou, Theodoros Evgeniou, and Massimiliano Pontil · 2008
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Exact matrix completion via convex optimization
Emmanuel J. Candès and Benjamin Recht · 2009
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A singular value thresholding algorithm for matrix completion
Jian-Feng Cai, Emmanuel J. Candès, and Zuowei Shen · 2010
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Matrix completion with noise
Emmanuel J. Candès and Yaniv Plan · 2010
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The power of convex relaxation: Near-optimal matrix completion
Emmanuel J. Candès and Terence Tao · 2010
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Matrix completion from noisy entries
Raghunandan H Keshavan, Andrea Montanari, and Sewoong Oh · 2010
Earlier work this paper cites.
Spectral regularization algorithms for learning large incomplete matrices
Rahul Mazumder, Trevor Hastie, and Robert Tibshirani · 2010
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Joint covariate selection and joint subspace selection for multiple classification problems
Guillaume Obozinski, Ben Taskar, and Michael I. Jordan · 2010
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Uniqueness of low-rank matrix completion by rigidity theory
Amit Singer and Mihai Cucuringu · 2010
Cited alongside, same era.
Learning with the weighted trace-norm under arbitrary sampling distributions
Rina Foygel, Ruslan Salakhutdinov, Ohad Shamir, and Nathan Srebro · 2011
Cited alongside, same era.
Von Neumann entropy penalization and low-rank matrix estimation
Vladimir Koltchinskii · 2011
Cited alongside, same era.
Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
Vladimir Koltchinskii, Karim Lounici, and Alexandre B. Tsybakov · 2011
Cited alongside, same era.
Estimation of (near) low-rank matrices with noise and high-dimensional scaling
Sahand Negahban and Martin J. Wainwright · 2011
Cited alongside, same era.
Estimation of high-dimensional low-rank matrices
Constructing confidence sets for the matrix completion problem
Alexandra Carpentier, Olga Klopp, and Matthias Löffler · 2016
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Identifiability of normal and normal mixture models with nonignorable missing data
Wang Miao, Peng Ding, and Zhi Geng · 2016
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A characterization of deterministic sampling patterns for low-rank matrix completion
Daniel L Pimentel-Alarcón, Nigel Boston, and Robert D. Nowak · 2016
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Asymptotic theory for estimating the singular vectors and values of a partially-observed low rank matrix with noise
Juhee Cho, Donggyu Kim, and Karl Rohe · 2017
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Adaptive estimation of noise variance and matrix estimation via usvt algorithm
Mona Azadkia · 2018
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Angelika Rohde and Alexandre B. Tsybakov · 2011
Cited alongside, same era.
Large networks and graph limits
László Lovász · 2012
Cited alongside, same era.
A novel bayesian similarity measure for recommender systems
Guibing Guo, Jie Zhang, and Neil Yorke-Smith · 2013
Cited alongside, same era.
Matrix completion from any given set of observations
Troy Lee and Adi Shraibman · 2013
Cited alongside, same era.
Universal matrix completion
Srinadh Bhojanapalli and Prateek Jain · 2014
Cited alongside, same era.
1-bit matrix completion
Mark A. Davenport, Yaniv Plan, Ewout Van Den Berg, and Mary Wootters · 2014
Cited alongside, same era.
Minimax risk of matrix denoising by singular value thresholding
David Donoho and Matan Gavish · 2014
Cited alongside, same era.
Estimation with incomplete data: The linear case
Karthika Mohan, Felix Thoemmes, and Judea Pearl · 2018
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Adapting to unknown noise distribution in matrix denoising
Andrea Montanari, Feng Ruan, and Jun Yan · 2018
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Wei Ma and George H Chen · 2019
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Low-rank matrix completion: A contemporary survey
Luong Trung Nguyen, Junhan Kim, and Byonghyo Shim · 2019
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High-dimensional principal component analysis with heterogeneous missingness
Ziwei Zhu, Tengyao Wang, and Richard J Samworth · 2019
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A deterministic theory of low rank matrix completion
Sourav Chatterjee · 2020
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CVXR: An R package for disciplined convex optimization
Anqi Fu, Balasubramanian Narasimhan, and Stephen Boyd · 2020
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Imputation and low-rank estimation with Missing Not At Random data
Aude Sportisse, Claire Boyer, and Julie Josse · 2020
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filling: Matrix Completion, Imputation, and Inpainting Methods , 2020
Kisung You · 2020
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Subspace estimation from unbalanced and incomplete data matrices: ℓ 2 , ∞ \ell_{2,\infty} statistical guarantees
Changxiao Cai, Gen Li, Yuejie Chi, H Vincent Poor, and Yuxin Chen · 2021
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Tenips: Inverse propensity sampling for tensor completion
Chengrun Yang, Lijun Ding, Ziyang Wu, and Madeleine Udell · 2021
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