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Generalized linear models (GLMs) arise in high-dimensional machine learning, statistics, communications and signal processing.
A mathematical theory of communication, part i, part ii
C. E. Shannon · 1948
Earlier work this paper cites.
The perceptron, a perceiving and recognizing automaton Project Para
F. Rosenblatt · 1957
Earlier work this paper cites.
Ordinary Differential Equations
P. Hartman · 1964
Earlier work this paper cites.
Generalized linear models
J. Nelder and R. Wedderburn · 1972
Earlier work this paper cites.
Solution of‘solvable model of a spin glass’
D. J. Thouless, P. W. Anderson, and R. G. Palmer · 1977
Earlier work this paper cites.
Phase retrieval algorithms: a comparison
J. R. Fienup · 1982
Earlier work this paper cites.
Generalized linear models
P. McCullagh · 1984
Earlier work this paper cites.
Spin glass theory and beyond
M. Mézard, G. Parisi, and M.-A. Virasoro · 1987
Earlier work this paper cites.
Three unfinished works on the optimal storage capacity of networks
E. Gardner and B. Derrida · 1989
Earlier work this paper cites.
The space of interactions in neural networks: Gardner’s computation with the cavity method
M. Mézard · 1989
Earlier work this paper cites.
First-order transition to perfect generalization in a neural network with binary synapses
G. Györgyi · 1990
Earlier work this paper cites.
Learning from examples in large neural networks
H. Sompolinsky, N. Tishby, and H. S. Seung · 1990
Earlier work this paper cites.
Generalization performance of bayes optimal classification algorithm for learning a perceptron
M. Opper and D. Haussler · 1991
Earlier work this paper cites.
The transition to perfect generalization in perceptrons
E. B. Baum and Y.-D. Lyuu · 1991
Earlier work this paper cites.
Statistical mechanics of learning from examples
H. S. Seung, H. Sompolinsky, and N. Tishby · 1992
Earlier work this paper cites.
Memorization without generalization in a multilayered neural network
D. Hansel, G. Mato, and C. Meunier · 1992
Earlier work this paper cites.
The statistical mechanics of learning a rule
T. L. H. Watkin, A. Rau, and M. Biehl · 1993
Earlier work this paper cites.
Reliability of replica symmetry for the generalization problem in a toy multilayer neural network
A. Engel and L. Reimers · 1994
Earlier work this paper cites.
Storage capacity and generalization error for the reversed-wedge ising perceptron
G. J. Bex, R. Serneels, and C. V. den Broeck · 1995
Earlier work this paper cites.
Mean field approach to bayes learning in feed-forward neural networks
M. Opper and O. Winther · 1996
Earlier work this paper cites.
The information bottleneck method
N. Tishby, F. C. Pereira, and W. Bialek · 1999
Earlier work this paper cites.
Statistical mechanics of learning
A. Engel and C. Van den Broeck · 2001
Earlier work this paper cites.
Tractable approximations for probabilistic models: The adaptive thouless-anderson-palmer mean field approach
M. Opper and O. Winther · 2001
Earlier work this paper cites.
Statistical mechanics of lossy data compression using a nonmonotonic perceptron
T. Hosaka, Y. Kabashima, and H. Nishimori · 2002
Earlier work this paper cites.
A statistical-mechanics approach to large-system analysis of cdma multiuser detectors
T. Tanaka · 2002
Earlier work this paper cites.
The thermodynamic limit in mean field spin glass models
F. Guerra and F. L. Toninelli · 2002
Earlier work this paper cites.
Envelope theorems for arbitrary choice sets
P. Milgrom and I. Segal · 2002
Earlier work this paper cites.
Concentration inequalities
S. Boucheron, G. Lugosi, and O. Bousquet · 2004
Earlier work this paper cites.
Sparse nonnegative solution of underdetermined linear equations by linear programming
D. L. Donoho and J. Tanner · 2005
Earlier work this paper cites.
Randomly spread cdma: Asymptotics via statistical physics
D. Guo and S. Verdú · 2005
Earlier work this paper cites.
Mutual information and minimum mean-square error in gaussian channels
D. Guo, S. Shamai, and S. Verdú · 2005
Earlier work this paper cites.
Near-optimal signal recovery from random projections: Universal encoding strategies?
E. J. Candes and T. Tao · 2006
Earlier work this paper cites.
A generalization of the lindeberg principle
S. Chatterjee et al · 2006
Earlier work this paper cites.
Efficient supervised learning in networks with binary synapses
C. Baldassi, A. Braunstein, N. Brunel, and R. Zecchina · 2007
Earlier work this paper cites.
Griffith-kelly-sherman correlation inequalities: A useful tool in the theory of error correcting codes
N. Macris · 2007
Earlier work this paper cites.
Measure theory
V. I. Bogachev · 2007
Cited alongside, same era.
1-bit compressive sensing
P. T. Boufounos and R. G. Baraniuk · 2008
Cited alongside, same era.
Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels
Y. Kabashima · 2008
Cited alongside, same era.
Modern coding theory
T. Richardson and R. Urbanke · 2008
Cited alongside, same era.
Graphical models, exponential families, and variational inference
M. J. Wainwright, M. I. Jordan, et al · 2008
Cited alongside, same era.
Estimating random variables from random sparse observations
A. Montanari · 2008
Cited alongside, same era.
Message-passing algorithms for compressed sensing
Stable optimizationless recovery from phaseless linear measurements
L. Demanet and P. Hand · 2014
Later among the works it cites.
Bayesian signal reconstruction for 1-bit compressed sensing
Y. Xu, Y. Kabashima, and L. Zdeborová · 2014
Later among the works it cites.
An iterative construction of solutions of the tap equations for the sherrington–kirkpatrick model
E. Bolthausen · 2014
Later among the works it cites.
Binary linear classification and feature selection via generalized approximate message passing
J. Ziniel, P. Schniter, and P. Sederberg · 2014
Later among the works it cites.
Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
Later among the works it cites.
Compressive phase retrieval via generalized approximate message passing
P. Schniter and S. Rangan · 2015
Later among the works it cites.
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D. L. Donoho, A. Maleki, and A. Montanari · 2009
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Information, physics, and computation
M. Mezard and A. Montanari · 2009
Cited alongside, same era.
Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing
D. Donoho and J. Tanner · 2009
Cited alongside, same era.
Exact solution of the gauge symmetric p-spin glass model on a complete graph
S. B. Korada and N. Macris · 2009
Cited alongside, same era.
Toward fast reliable communication at rates near capacity with gaussian noise
A. R. Barron and A. Joseph · 2010
Cited alongside, same era.
Rényi information dimension: Fundamental limits of almost lossless analog compression
Y. Wu and S. Verdú · 2010
Cited alongside, same era.
Universality in polytope phase transitions and message passing algorithms
M. Bayati, M. Lelarge, and A. Montanari · 2015
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Simultaneously structured models with application to sparse and low-rank matrices
S. Oymak, A. Jalali, M. Fazel, Y. C. Eldar, and B. Hassibi · 2015
Later among the works it cites.
Convex analysis
R. T. Rockafellar · 2015
Later among the works it cites.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng · 2015
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Statistical physics of inference: thresholds and algorithms
L. Zdeborová and F. Krzakala · 2016
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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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An equivalence between high dimensional bayes optimal inference and m-estimation
M. Advani and S. Ganguli · 2016
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Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes
C. Baldassi, C. Borgs, J. T. Chayes, A. Ingrosso, C. Lucibello, L. Saglietti, and R. Zecchina · 2016
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Threshold saturation of spatially coupled sparse superposition codes for all memoryless channels
J. Barbier, M. Dia, and N. Macris · 2016
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The mutual information in random linear estimation
J. Barbier, M. Dia, N. Macris, and F. Krzakala · 2016
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The replica-symmetric prediction for compressed sensing with gaussian matrices is exact
G. Reeves and H. D. Pfister · 2016
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CVXPY: A Python-embedded modeling language for convex optimization
S. Diamond and S. Boyd · 2016
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Phasemax: Convex phase retrieval via basis pursuit
T. Goldstein and C. Studer · 2016
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Fundamental limits of symmetric low-rank matrix estimation
M. Lelarge and L. Miolane · 2016
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Rethinking generalization requires revisiting old ideas: statistical mechanics approaches and complex learning behavior
C. H. Martin and M. W. Mahoney · 2017
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Mutual information and optimality of approximate message-passing in random linear estimation
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Information-theoretic thresholds from the cavity method
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https://github.com/sphinxteam/GeneralizedLinearModel2017 , 2017
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