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It has been observed that the performances of many high-dimensional estimation problems are universal with respect to underlying sensing (or design) matrices.
Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing
David Donoho and Jared Tanner · 1906
Earlier work this paper cites.
Eine neue herleitung des exponentialgesetzes in der wahrscheinlichkeitsrechnung
Jarl Waldemar Lindeberg · 1922
Earlier work this paper cites.
A problem in geometric probability
James G Wendel · 1962
Earlier work this paper cites.
Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition
Thomas M. Cover · 1965
Earlier work this paper cites.
Partitions of N-space by hyperplanes
Robert O Winder · 1966
Earlier work this paper cites.
Distribution of eigenvalues for some sets of random matrices
Vladimir A Marčenko and Leonid Andreevich Pastur · 1967
Earlier work this paper cites.
Phase retrieval algorithms: a comparison
James R Fienup · 1982
Earlier work this paper cites.
Asymptotics of graphical projection pursuit
Persi Diaconis and David Freedman · 1984
Earlier work this paper cites.
On majorization and Schur products
Ravindra B Bapat and Vaikalathur S Sunder · 1985
Earlier work this paper cites.
Some inequalities for Gaussian processes and applications
Yehoram Gordon · 1985
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Limiting spectral distribution for a class of random matrices
Yong Q Yin · 1986
Earlier work this paper cites.
Maximum likelihood estimation of linear signal parameters for Poisson processes
Michael Unser and Murray Eden · 1988
Earlier work this paper cites.
Limit laws for random matrices and free products
Dan Voiculescu · 1991
Earlier work this paper cites.
Perturbation bounds for matrix square roots and Pythagorean sums
Bernhard A Schmitt · 1992
Earlier work this paper cites.
Free random variables. a noncommutative probability approach to free products with applications to random matrices, operator algebras and harmonic analysis on free groups. crm monograph series, 1
Dan V Voiculescu, KJ Dykema, and Alexandru Nica · 1992
Earlier work this paper cites.
Replica field theory for deterministic models II. a non-random spin glass with glassy behaviour
Enzo Marinari, Giorgio Parisi, and Felix Ritort · 1994
Earlier work this paper cites.
Mean-field equations for spin models with orthogonal interaction matrices
Giorgio Parisi and Marc Potters · 1995
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Recursive consistent estimation with bounded noise
Sundeep Rangan and Vivek K Goyal · 2001
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Grassmannian frames with applications to coding and communication
Thomas Strohmer and Robert W Heath Jr · 2003
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Universality in Sherrington–Kirkpatrick’s spin glass model
Philippe Carmona and Yueyun Hu · 2005
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A simple invariance theorem
Sourav Chatterjee · 2005
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Neighborly polytopes and sparse solutions of underdetermined linear equations
David L. Donoho · 2005
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Randomly spread CDMA: Asymptotics via statistical physics
Dongning Guo and Sergio Verdú · 2005
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High-dimensional centrally symmetric polytopes with neighborliness proportional to dimension
David L Donoho · 2006
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Cedric Gerbelot, Alia Abbara, and Florent Krzakala · 2006
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Analysis of CDMA systems that are characterized by eigenvalue spectrum
Koujin Takeda, Shinsuke Uda, and Yoshiyuki Kabashima · 2006
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The lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano, Andrea Montanari, and Yuting Wei · 2007
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Limit of the smallest eigenvalue of a large dimensional sample covariance matrix
Zhi-Dong Bai and Yong-Qua Yin · 2008
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On sparse reconstruction from Fourier and Gaussian measurements
Mark Rudelson and Roman Vershynin · 2008
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Chirp sensing codes: Deterministic compressed sensing measurements for fast recovery
Lorne Applebaum, Stephen D Howard, Stephen Searle, and Robert Calderbank · 2009
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Corrections to LRT on large-dimensional covariance matrix by RMT
Zhidong Bai, Dandan Jiang, Jian-Feng Yao, and Shurong Zheng · 2009
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Message-passing algorithms for compressed sensing
David L Donoho, Arian Maleki, and Andrea Montanari · 2009
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Universality laws for high-dimensional learning with random features
Hong Hu and Yue M Lu · 2009
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A fast and efficient algorithm for low-rank approximation of a matrix
Nam H Nguyen, Thong T Do, and Trac D Tran · 2009
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Asymptotic analysis of MAP estimation via the replica method and compressed sensing
Sundeep Rangan, Vivek Goyal, and Alyson K Fletcher · 2009
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Construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property
Robert Calderbank, Stephen Howard, and Sina Jafarpour · 2010
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Counting the faces of randomly-projected hypercubes and orthants, with applications
David L Donoho and Jared Tanner · 2010
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Capacity of channels with frequency-selective and time-selective fading
Antonia M Tulino, Giuseppe Caire, Shlomo Shamai, and Sergio Verdú · 2010
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Limiting empirical singular value distribution of restrictions of discrete Fourier transform matrices
Brendan Farrell · 2011
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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
Nathan Halko, Per-Gunnar Martinsson, and Joel A Tropp · 2011
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Noureddine El Karoui and Holger Kösters · 2011
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Applications of the Lindeberg principle in communications and statistical learning
Satish Babu Korada and Andrea Montanari · 2011
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Bits from photons: Oversampled image acquisition using binary Poisson statistics
Feng Yang, Yue M Lu, Luciano Sbaiz, and Martin Vetterli · 2011
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Introduction to finite frame theory
Peter G Casazza, Gitta Kutyniok, and Friedrich Philipp · 2012
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The convex geometry of linear inverse problems
Venkat Chandrasekaran, Benjamin Recht, Pablo A Parrilo, and Alan S Willsky · 2012
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Likelihood ratio tests for covariance matrices of high-dimensional normal distributions
Dandan Jiang, Tiefeng Jiang, and Fan Yang · 2012
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The road to deterministic matrices with the restricted isometry property
Afonso S Bandeira, Matthew Fickus, Dustin G Mixon, and Percy Wong · 2013
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Optimal M-estimation in high-dimensional regression
Derek Bean, Peter J Bickel, Noureddine El Karoui, and Bin Yu · 2013
Ridge regression: Structure, cross-validation, and sketching
Sifan Liu and Edgar Dobriban · 2019
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Optimal spectral initialization for signal recovery with applications to phase retrieval
Wangyu Luo, Wael Alghamdi, and Yue M Lu · 2019
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Optimization-based AMP for phase retrieval: The impact of initialization and ℓ 2 \ell_{2} regularization
Junjie Ma, Ji Xu, and Arian Maleki · 2019
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Vector approximate message passing
Sundeep Rangan, Philip Schniter, and Alyson K Fletcher · 2019
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The replica-symmetric prediction for random linear estimation with Gaussian matrices is exact
Galen Reeves and Henry D Pfister · 2019
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A modern maximum-likelihood theory for high-dimensional logistic regression
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Information-theoretically optimal compressed sensing via spatial coupling and approximate message passing
David L Donoho, Adel Javanmard, and Andrea Montanari · 2013
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On robust regression with high-dimensional predictors
Noureddine El Karoui, Derek Bean, Peter J Bickel, Chinghway Lim, and Bin Yu · 2013
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State evolution for general approximate message passing algorithms, with applications to spatial coupling
Adel Javanmard and Andrea Montanari · 2013
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Central limit theorems for classical likelihood ratio tests for high-dimensional normal distributions
Tiefeng Jiang and Fan Yang · 2013
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Noureddine El Karoui · 2013
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Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices
Hatef Monajemi, Sina Jafarpour, Matan Gavish, Stat 330/CME 362 Collaboration, David L Donoho, Sivaram Ambikasaran, Sergio Bacallado, Dinesh Bharadia, Yuxin Chen, Young Choi, et al · 2013
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Pragya Sur and Emmanuel J Candès · 2019
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The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled chi-square
Pragya Sur, Yuxin Chen, and Emmanuel J Candès · 2019
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On the universality of noiseless linear estimation with respect to the measurement matrix
Alia Abbara, Antoine Baker, Florent Krzakala, and Lenka Zdeborová · 2020
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State evolution for approximate message passing with non-separable functions
Raphael Berthier, Andrea Montanari, and Phan-Minh Nguyen · 2020
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Algorithmic analysis and statistical estimation of SLOPE via approximate message passing
Zhiqi Bu, Jason M Klusowski, Cynthia Rush, and Weijie J Su · 2020
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The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
Emmanuel J Candès and Pragya Sur · 2020
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Optimal iterative sketching methods with the subsampled randomized Hadamard transform
Jonathan Lacotte, Sifan Liu, Edgar Dobriban, and Mert Pilanci · 2020
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Phase transitions of spectral initialization for high-dimensional non-convex estimation
Yue M Lu and Gen Li · 2020
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Phase retrieval in high dimensions: Statistical and computational phase transitions
Antoine Maillard, Bruno Loureiro, Florent Krzakala, and Lenka Zdeborová · 2020
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The role of regularization in classification of high-dimensional noisy Gaussian mixture
Francesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, and Lenka Zdeborova · 2020
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Convolutional approximate message-passing
Keigo Takeuchi · 2020
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Which bridge estimator is the best for variable selection?
Shuaiwen Wang, Haolei Weng, and Arian Maleki · 2020
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The high-dimensional asymptotics of first order methods with random data
Michael Celentano, Chen Cheng, and Andrea Montanari · 2021
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Universality of approximate message passing algorithms
Wei-Kuo Chen and Wai-Kit Lam · 2021
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Graph-based approximate message passing iterations
Cédric Gerbelot and Raphaël Berthier · 2021
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Likelihood ratio test in multivariate linear regression: from low to high dimension
Yinqiu He, Tiefeng Jiang, Jiyang Wen, and Gongjun Xu · 2021
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Minimum ℓ 1 \ell_{1} -norm interpolators: Precise asymptotics and multiple descent
Yue Li and Yuting Wei · 2021
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Householder dice: A matrix-free algorithm for simulating dynamics on Gaussian and random orthogonal ensembles
Yue M Lu · 2021
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PCA initialization for approximate message passing in rotationally invariant models
Marco Mondelli and Ramji Venkataramanan · 2021
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Optimal combination of linear and spectral estimators for generalized linear models
Marco Mondelli, Christos Thrampoulidis, and Ramji Venkataramanan · 2021
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Fundamental limits of ridge-regularized empirical risk minimization in high dimensions
Hossein Taheri, Ramtin Pedarsani, and Christos Thrampoulidis · 2021
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Bayes-optimal convolutional AMP
Keigo Takeuchi · 2021
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Universality of linearized message passing for phase retrieval with structured sensing matrices
Rishabh Dudeja and Milad Bakhshizadeh · 2022
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Universality of approximate message passing with semi-random matrices
Rishabh Dudeja, Yue M Lu, and Subhabrata Sen · 2022
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Approximate message passing algorithms for rotationally invariant matrices
Zhou Fan · 2022
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A unifying tutorial on approximate message passing
Oliver Y Feng, Ramji Venkataramanan, Cynthia Rush, and Richard J Samworth · 2022
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Gaussian universality of linear classifiers with random labels in high-dimension
Federica Gerace, Florent Krzakala, Bruno Loureiro, Ludovic Stephan, and Lenka Zdeborová · 2022
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Universality of regularized regression estimators in high dimensions
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Slope for sparse linear regression: Asymptotics and optimal regularization
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A precise high-dimensional asymptotic theory for boosting and minimum- ℓ 1 \ell_{1} -norm interpolated classifiers
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Memory AMP
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Construction of optimal spectral methods in phase retrieval
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The generalization error of random features regression: Precise asymptotics and the double descent curve
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Universality of empirical risk minimization
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