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Robust Volume Minimization-Based Matrix Factorization for Remote Sensing and Document Clustering

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Outgoing claims: the papers this work cites, builds on, or argues with.

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nonlinear programming
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Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization
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inferredcites →https://doi.org/10.1109/tgrs.2011.2151197openalex-snapshot
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inferredcites →https://doi.org/10.1109/tgrs.2015.2424719openalex-snapshot
Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No-Pure-Pixel Case
inferredcites →https://doi.org/10.1109/tip.2015.2468177openalex-snapshot
Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization
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inferredcites →https://doi.org/10.1109/tnn.2011.2164621openalex-snapshot
Minimum-Volume-Constrained Nonnegative Matrix Factorization: Enhanced Ability of Learning Parts
inferredcites →https://doi.org/10.1109/tpami.2012.88openalex-snapshot
Robust Recovery of Subspace Structures by Low-Rank Representation
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Robust iterative fitting of multilinear models
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A Convex Analysis-Based Minimum-Volume Enclosing Simplex Algorithm for Hyperspectral Unmixing
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Blind Separation of Quasi-Stationary Sources: Exploiting Convex Geometry in Covariance Domain
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A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization
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Document clustering by concept factorization
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Robust principal component analysis?
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Proximal Algorithms
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A Smoothing SQP Framework for a Class of Composite $L_q$ Minimization over Polyhedron
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When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts?

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Polymer sequencing via unsupervised learning of pyrolysis-mass spectra
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