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IGARSS
2009
13 years 5 months ago
Unmixing Sparse Hyperspectral Mixtures
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...
Marian-Daniel Iordache, José M. Bioucas-Dia...
FOCM
2011
175views more  FOCM 2011»
13 years 2 months ago
Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...
Donald Goldfarb, Shiqian Ma
MP
2011
13 years 2 months ago
Null space conditions and thresholds for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
SIAMIS
2011
13 years 2 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang
SIAMIS
2010
190views more  SIAMIS 2010»
13 years 2 months ago
Analysis and Generalizations of the Linearized Bregman Method
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Wotao Yin