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Proof methods for robust low-rank matrix recovery (Q2106469)

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Language	Label	Description	Also known as
English	Proof methods for robust low-rank matrix recovery	scientific article

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scholarly article

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Proof methods for robust low-rank matrix recovery (English)

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Dominik Stöger

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publication date

14 December 2022

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full work available at URL

https://arxiv.org/abs/2106.04382

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zbMATH Keywords

low-rank matrix recovery problems

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reconstruction performance

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Blind Deconvolution Using Convex Programming

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Living on the edge: phase transitions in convex programs with random data

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Convex multi-task feature learning

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Painless reconstruction from magnitudes of frame coefficients

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A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization

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Optimal rates of convergence for noisy sparse phase retrieval via thresholded Wirtinger flow

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Phase Retrieval via Matrix Completion

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Solving quadratic equations via phaselift when there are about as many equations as unknowns

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Phase retrieval from coded diffraction patterns

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Phase Retrieval via Wirtinger Flow: Theory and Algorithms

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A Probabilistic and RIPless Theory of Compressed Sensing

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Exact matrix completion via convex optimization

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Stable signal recovery from incomplete and inaccurate measurements

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PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming

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Decoding by Linear Programming

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The Power of Convex Relaxation: Near-Optimal Matrix Completion

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The convex geometry of linear inverse problems

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Incoherence-Optimal Matrix Completion

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Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems

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Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization

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An algebraic characterization of injectivity in phase retrieval

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Phase retrieval: stability and recovery guarantees

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Non-Bayesian Activity Detection, Large-Scale Fading Coefficient Estimation, and Unsourced Random Access With a Massive MIMO Receiver

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Low-rank Matrix Recovery via Iteratively Reweighted Least Squares Minimization

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A mathematical introduction to compressive sensing

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Sparse power factorization: balancing peakiness and sample complexity

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Recovering Low-Rank Matrices From Few Coefficients in Any Basis

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A partial derandomization of phaselift using spherical designs

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Improved recovery guarantees for phase retrieval from coded diffraction patterns

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Low-rank matrix completion using alternating minimization

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Localization from incomplete noisy distance measurements

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Blind Demixing and Deconvolution at Near-Optimal Rate

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Stable low-rank matrix recovery via null space properties

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Explicit frames for deterministic phase retrieval via PhaseLift

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Optimal Injectivity Conditions for Bilinear Inverse Problems with Applications to Identifiability of Deconvolution Problems

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Matrix Completion From a Few Entries

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Noisy low-rank matrix completion with general sampling distribution

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Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion

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Bounding the Smallest Singular Value of a Random Matrix Without Concentration

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Phase Retrieval Without Small-Ball Probability Assumptions

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Suprema of Chaos Processes and the Restricted Isometry Property

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On the Convex Geometry of Blind Deconvolution and Matrix Completion

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Complex phase retrieval from subgaussian measurements

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Robust Nonnegative Sparse Recovery and the Nullspace Property of 0/1 Measurements

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Low rank matrix recovery from rank one measurements

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Blind Recovery of Sparse Signals From Subsampled Convolution

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Identifiability in Bilinear Inverse Problems With Applications to Subspace or Sparsity-Constrained Blind Gain and Phase Calibration

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Blind Deconvolution Meets Blind Demixing: Algorithms and Performance Bounds

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Implicit regularization in nonconvex statistical estimation: gradient descent converges linearly for phase retrieval, matrix completion, and blind deconvolution

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Learning without Concentration

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Sparse Approximate Solutions to Linear Systems

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Simultaneously Structured Models With Application to Sparse and Low-Rank Matrices

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A Simpler Approach to Matrix Completion

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Guaranteed Matrix Completion via Non-Convex Factorization

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User-friendly tail bounds for sums of random matrices

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Convex Recovery of a Structured Signal from Independent Random Linear Measurements

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Practical Sketching Algorithms for Low-Rank Matrix Approximation

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Characterization of the subdifferential of some matrix norms

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Identifiers

zbMATH Open document ID

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10.1007/978-3-031-09745-4_2

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:2106469

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