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We analyse the matrix factorization problem.
A general approach to confirmatory maximum likelihood factor analysis
Jöreskog K. G · 1969
Earlier work this paper cites.
Maximum Likelihood from Incomplete Data via the EM Algorithm
Dempster A., Laird N. & Rubin D · 1977
Earlier work this paper cites.
Solution of ‘Solvable Model of a Spin-Glass’
Thouless D. J., Anderson P. W. & Palmer R. G · 1977
Earlier work this paper cites.
SK Model: The Replica Solution without Replicas
Mézard M., Parisi G. & Virasoro M. A · 1986
Earlier work this paper cites.
Spin-Glass Theory and Beyond , vol. 9 (World Scientific, Singapore, 1987)
Mézard M., Parisi G. & Virasoro M. A · 1987
Earlier work this paper cites.
Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise
Opper M. & Haussler D · 1991
Earlier work this paper cites.
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen B. A. et al · 1996
Earlier work this paper cites.
Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1
Olshausen B. A. & Field D. J · 1997
Earlier work this paper cites.
A blind source separation technique using second-order statistics
Belouchrani A., Abed-Meraim K., Cardoso J.-F. & Moulines E · 1997
Earlier work this paper cites.
Method of optimal directions for frame design
Engan K., Aase S. O. & Husoy J. H · 1999
Earlier work this paper cites.
Blind source separation of more sources than mixtures using overcomplete representations
Lee T.-W., Lewicki M. S., Girolami M. & Sejnowski T. J · 1999
Earlier work this paper cites.
The Nishimori line and Bayesian statistics
Iba Y · 1999
Earlier work this paper cites.
Learning overcomplete representations
Lewicki M. S. & Sejnowski T. J · 2000
Earlier work this paper cites.
Blind source separation by sparse decomposition in a signal dictionary
Zibulevsky M. & Pearlmutter B. A · 2001
Earlier work this paper cites.
Underdetermined blind source separation using sparse representations
Bofill P. & Zibulevsky M · 2001
Earlier work this paper cites.
Statistical Physics of Spin Glasses and Information Processing (Oxford University Press, Oxford, 2001)
Nishimori H · 2001
Earlier work this paper cites.
The ζ \zeta (2) limit in the random assignment problem
Aldous D. J · 2001
Earlier work this paper cites.
Factor graphs and the sum-product algorithm
Kschischang F. R., Frey B. & Loeliger H.-A · 2001
Earlier work this paper cites.
Analytic and Algorithmic Solution of Random Satisfiability Problems
Mézard M., Parisi G. & Zecchina R · 2002
Earlier work this paper cites.
A statistical-mechanics approach to large-system analysis of CDMA multiuser detectors
Tanaka T · 2002
Earlier work this paper cites.
Dictionary learning algorithms for sparse representation
Kreutz-Delgado K. et al · 2003
Earlier work this paper cites.
Understanding Belief Propagation and Its Generalizations
Yedidia J., Freeman W. & Weiss Y · 2003
Earlier work this paper cites.
Randomly spread CDMA: Asymptotics via statistical physics
Guo D. & Verdú S · 2005
Earlier work this paper cites.
Sparse component analysis and blind source separation of underdetermined mixtures
Georgiev P., Theis F. & Cichocki A · 2005
Earlier work this paper cites.
Adaptive Damping and Mean Removal for the Generalized Approximate Message Passing Algorithm (2014)
Vila J., Schniter P., Rangan S., Krzakala F. & Zdeborová L · 2005
Earlier work this paper cites.
Sparse principal component analysis
Zou H., Hastie T. & Tibshirani R · 2006
Cited alongside, same era.
Analysis of belief propagation for non-linear problems: The example of CDMA (or: How to prove Tanaka’s formula)
Montanari A. & Tse D · 2006
Cited alongside, same era.
K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
Aharon M., Elad M. & Bruckstein A. M · 2006
Cited alongside, same era.
On the uniqueness of overcomplete dictionaries, and a practical way to retrieve them
Michal Aharon, Michael Elad A. M. B · 2006
Cited alongside, same era.
A survey of sparse component analysis for blind source separation: principles, perspectives, and new challenges
Gribonval R., Lesage S. et al · 2006
Cited alongside, same era.
A direct formulation for sparse PCA using semidefinite programming
Bilinear Generalized Approximate Message Passing (BiG-AMP) for Matrix Recovery Problem
Schniter P., Parker J. & Cevher V · 2012
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Sparse and Redundant Representation Modeling—What Next?
Elad M · 2012
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Local stability and robustness of sparse dictionary learning in the presence of noise
Jenatton R., Gribonval R. & Bach F · 2012
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Iterative estimation of constrained rank-one matrices in noise
Rangan S. & Fletcher A. K · 2012
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Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing
Donoho D. L., Javanmard A. & Montanari A · 2012
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d’Aspremont A., El Ghaoui L., Jordan M. I. & Lanckriet G. R · 2007
Cited alongside, same era.
Modern Coding Theory (Cambridge University Press, 2008)
Richardson T. & Urbanke R · 2008
Cited alongside, same era.
Estimating random variables from random sparse observations
Montanari A · 2008
Cited alongside, same era.
Exact matrix completion via convex optimization
Candès E. J. & Recht B · 2009
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Message-passing algorithms for compressed sensing
Donoho D. L., Maleki A. & Montanari A · 2009
Cited alongside, same era.
Information, Physics, and Computation (Oxford Press, Oxford, 2009)
Mézard M. & Montanari A · 2009
Cited alongside, same era.
Sparse and low-rank matrix decompositions
Chandrasekaran V., Sanghavi S., Parrilo P. A. & Willsky A. S · 2009
Cited alongside, same era.
Krzakala F., Mézard M., Sausset F., Sun Y. & Zdeborová L · 2012
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Representation learning: A review and new perspectives
Bengio Y., Courville A. & Vincent P · 2013
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Sample complexity of Bayesian optimal dictionary learning
Sakata A. & Kabashima Y · 2013
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Phase diagram and approximate message passing for blind calibration and dictionary learning
Krzakala F., Mézard M. & Zdeborová L · 2013
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Bilinear generalized approximate message passing—Part I: Derivation
Parker J., Schniter P. & Cevher V · 2013
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Exact recovery of sparsely-used dictionaries
Spielman D. A., Wang H. & Wright J · 2013
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New algorithms for learning incoherent and overcomplete dictionaries
Arora S., Ge R. & Moitra A · 2013
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Exact Recovery of Sparsely Used Overcomplete Dictionaries
Agarwal A., Anandkumar A. & Netrapalli P · 2013
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Sample complexity of dictionary learning and other matrix factorizations
Gribonval R., Jenatton R., Bach F., Kleinsteuber M. & Seibert M · 2013
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Fixed points of generalized approximate message passing with arbitrary matrices
Rangan S., Schniter P., Riegler E., Fletcher A. & Cevher V · 2013
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Bilinear generalized approximate message passing—Part II: Applications
Parker J., Schniter P. & Cevher V · 2014
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Proof of the satisfiability conjecture for large k
Ding J., Sly A. & Sun N · 2014
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1-bit matrix completion
Davenport M. A., Plan Y., van den Berg E. & Wootters M · 2014
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Information-theoretically Optimal Sparse PCA
Deshpande Y. & Montanari A · 2014
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Variational Free Energies for Compressed Sensing
Krzakala F., Manoel A., Tramel E. W. & Zdeborová L · 2014
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On Convergence of Approximate Message Passing
Caltagirone F., Krzakala F. & Zdeborová L · 2014
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Deep learning
LeCun Y., Bengio Y. & Hinton G · 2015
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An overview of low-rank matrix recovery from incomplete observations (2015)
Davenport M. & Romberg J · 2015
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MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel
Lesieur T., Krzakala F. & Zdeborová L · 2015
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