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Matrix completion, where we wish to recover a low rank matrix by observing a few entries from it, is a widely studied problem in both theory and practice with wide applications.
Fast online svd revisions for lightweight recommender systems
Matthew Brand · 2003
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Amazon.com recommendations: item-to-item collaborative filtering
G. Linden, B. Smith, and J. York · 2003
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Exact matrix completion via convex optimization
Emmanuel J. Candès and Benjamin Recht · 2009
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The BellKor solution to the Netflix grand prize, 2009
Yehuda Koren · 2009
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A simple approach to matrix completion, 2009
Benjamin Recht · 2009
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The youtube video recommendation system
James Davidson, Benjamin Liebald, Junning Liu, Palash Nandy, Taylor Van Vleet, Ullas Gargi, Sujoy Gupta, Yu He, Mike Lambert, Blake Livingston, et al · 2010
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Robust video denoising using low rank matrix completion
Hui Ji, Chaoqiang Liu, Zuowei Shen, and Yuhong Xu · 2010
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Online learning for matrix factorization and sparse coding
Julien Mairal, Francis Bach, Jean Ponce, and Guillermo Sapiro · 2010
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Efficient algorithms for collaborative filtering
Raghunandan Hulikal Keshavan · 2012
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Incremental collaborative filtering recommender based on regularized matrix factorization
Xin Luo, Yunni Xia, and Qingsheng Zhu · 2012
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User-friendly tail bounds for sums of random matrices
Joel A Tropp · 2012
Cited alongside, same era.
Low-rank matrix and tensor completion via adaptive sampling
Akshay Krishnamurthy and Aarti Singh · 2013
Cited alongside, same era.
Parallel stochastic gradient algorithms for large-scale matrix completion
Benjamin Recht and Christopher Ré · 2013
Cited alongside, same era.
Global convergence of stochastic gradient descent for some non-convex matrix problems
Christopher De Sa, Kunle Olukotun, and Christopher Ré · 2014
Cited alongside, same era.
Understanding alternating minimization for matrix completion
Phase retrieval via matrix completion
Emmanuel J Candes, Yonina C Eldar, Thomas Strohmer, and Vladislav Voroninski · 2015
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Escaping from saddle points—online stochastic gradient for tensor decomposition
Rong Ge, Furong Huang, Chi Jin, and Yang Yuan · 2015
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Computing matrix squareroot via non convex local search
Prateek Jain, Chi Jin, Sham M Kakade, and Praneeth Netrapalli · 2015
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Guaranteed matrix completion via nonconvex factorization
Ruoyu Sun and Zhi-Quan Luo · 2015
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Streaming, memory limited matrix completion with noise
Se-Young Yun, Marc Lelarge, and Alexandre Proutiere · 2015
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Marcus Hardt · 2014
Cited alongside, same era.
Computational limits for matrix completion
Moritz Hardt, Raghu Meka, Prasad Raghavendra, and Benjamin Weitz · 2014
Cited alongside, same era.
Fast exact matrix completion with finite samples
Prateek Jain and Praneeth Netrapalli · 2014
Cited alongside, same era.
Simple, efficient, and neural algorithms for sparse coding
Sanjeev Arora, Rong Ge, Tengyu Ma, and Ankur Moitra · 2015
Cited alongside, same era.
Matrix completion has no spurious local minimum
Rong Ge, Jason D. Lee, and Tengyu Ma · 2016
Closest in time.
Prateek Jain, Chi Jin, Sham M Kakade, Praneeth Netrapalli, and Aaron Sidford · 2016
Closest in time.
Gradient descent converges to minimizers
Jason D Lee, Max Simchowitz, Michael I Jordan, and Benjamin Recht · 2016
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Gradient descent converges to minimizers: The case of non-isolated critical points
Ioannis Panageas and Georgios Piliouras · 2016
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