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Approximate Message Passing (AMP) algorithms are a class of iterative procedures for computationally-efficient estimation in high-dimensional inference and estimation tasks.
Message passing algorithms for compressed sensing
D. L. Donoho, A. Maleki, and A. Montanari · 2009
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Generalized approximate message passing for estimation with random linear mixing
S. Rangan · 2010
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The dynamics of message passing on dense graphs, with applications to compressed sensing
M. Bayati and A. Montanari · 2011
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An iterative construction of solutions of the TAP equations for the Sherrington-Kirkpatrick model
E. Bolthausen · 2012
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Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices
F. Krzakala, M. Mézard, F. Sausset, Y. Sun, and L. Zdeborová · 2012
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Graphical models concepts in compressed sensing
A. Montanari · 2012
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Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing
D. L. Donoho, A. Javanmard, and A. Montanari · 2013
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State evolution for general approximate message passing algorithms, with applications to spatial coupling
A. Javanmard and A. Montanari · 2013
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Universality in polytope phase transitions and message passing algorithms
M. Bayati, M. Lelarge, and A. Montanari · 2015
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Universality in polytope phase transitions and message passing algorithms
M. Bayati, M. Lelarge, and A. Montanari · 2015
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High dimensional robust m-estimation: Asymptotic variance via approximate message passing
D. Donoho and A. Montanari · 2016
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A theory of solving tap equations for ising models with general invariant random matrices
M. Opper, B. Cakmak, and O. Winther · 2016
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Finite sample analysis of approximate message passing algorithms
C. Rush and R. Venkataramanan · 2016
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Generalized approximate message-passing decoder for universal sparse superposition codes
E. Biyik, J. Barbier, and M. Dia · 2017
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Plug-in estimation in high-dimensional linear inverse problems: A rigorous analysis
A. Fletcher, P. Pandit, S. Rangan, S. Sarkar, and P. Schniter · 2017
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Learning and free energies for vector approximate message passing
A. Fletcher and P. Schniter · 2017
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Orthogonal amp
J. Ma and L. Ping · 2017
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Multi-layer generalized linear estimation
A. Manoel, F. Krzakala, M. Mézard, and L. Zdeborová · 2017
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Vector approximate message passing
S. Rangan, A. K. Fletcher, V. K. Goyal, E. Byrne, and P. Schniter · 2017
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Inference for generalized linear models via alternating directions and bethe free energy minimization
S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov · 2017
Cited alongside, same era.
The error exponent of sparse regression codes with amp decoding
C. Rush and R. Venkataramanan · 2017
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
E. J. Candès and P. Sur · 2020
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Universality of approximate message passing algorithms
W.-K. Chen and W.-K. Lam · 2021
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Approximate message passing with spectral initialization for generalized linear models
M. Mondelli and R. Venkataramanan · 2021
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Pca initialization for approximate message passing in rotationally invariant models
M. Mondelli and R. Venkataramanan · 2021
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Universality of approximate message passing with semi-random matrices
R. Dudeja, Y. M. Lu, and S. Sen · 2022
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Cited alongside, same era.
Vector approximate message passing for the generalized linear model
P. Schniter, S. Rangan, and A. Fletcher · 2017
Cited alongside, same era.
Rigorous dynamics and consistent estimation in arbitrarily conditioned linear systems
A. Fletcher, M. Sahraee-Ardakan, S. Rangan, and P. Schniter · 2018
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Inference in deep networks in high dimensions
A. K. Fletcher, S. Rangan, and P. Schniter · 2018
Cited alongside, same era.
Optimal errors and phase transitions in high-dimensional generalized linear models
J. Barbier, F. Krzakala, N. Macris, L. Miolane, and L. Zdeborová · 2019
Cited alongside, same era.
Analysis of approximate message passing with non-separable denoisers and markov random field priors
Y. Ma, C. Rush, and D. Baron · 2019
Cited alongside, same era.
A modern maximum-likelihood theory for high-dimensional logistic regression
P. Sur and E. J. Candès · 2019
Cited alongside, same era.
Z. Fan · 2022
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A unifying tutorial on approximate message passing
O. Y. Feng, R. Venkataramanan, C. Rush, R. J. Samworth, et al · 2022
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Sparse superposition codes under vamp decoding with generic rotational invariant coding matrices
T. Hou, Y. Liu, T. Fu, and J. Barbier · 2022
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A non-asymptotic framework for approximate message passing in spiked models
G. Li and Y. Wei · 2022
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Rigorous state evolution analysis for approximate message passing with side information
H. Liu, C. Rush, and D. Baron · 2022
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Optimal combination of linear and spectral estimators for generalized linear models
M. Mondelli, C. Thrampoulidis, and R. Venkataramanan · 2022
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Estimation in rotationally invariant generalized linear models via approximate message passing
R. Venkataramanan, K. Kögler, and M. Mondelli · 2022
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Universality of approximate message passing algorithms and tensor networks
T. Wang, X. Zhong, and Z. Fan · 2022
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Precise asymptotics for spectral methods in mixed generalized linear models
Y. Zhang, M. Mondelli, and R. Venkataramanan · 2022
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