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A direct method for sparse least squares problems with lower and upper bounds
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A factorization method for the solution of constrained linear least squares problems allowing subsequent data changes
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On the solution of large, structured linear complementarity problems: The block partitioned case
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An algorithm for linear least squares problems with equality and nonnegativity constraints
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Solving the minimal least squares problem subject to bounds on the variables
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Solution of sparse linear least squares problems using givens rotations
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A generalized conjugate gradient algorithm for solving a class of quadratic programming problems
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Rank and null space calculations using matrix decomposition without column interchanges
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Stability analysis of the method of seminormal equations for linear least squares problems
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Proceedings of the Computer Science and Statistics: 12th Annual Symposium on the Interface
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Methods for Modifying Matrix Factorizations
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On the Numerical Solution of Constrained Least-Squares Problems
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Perturbation Bounds for the $QR$ Factorization of a Matrix
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On Row and Column Orderings for Sparse Least Squares Problems
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Some Extensions of an Algorithm for Sparse Linear Least Squares Problems
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Numerical Methods for Large Sparse Linear Least Squares Problems
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Sparse Matrix Methods in Optimization
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Solving Least Squares Problems
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Predicting fill for sparse orthogonal factorization
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Very Large Least Squares Problems and Supercomputers,
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Computer Solution of Large Sparse Positive Definite Systems.
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Sparse Linear Least Squares Problems in Optimization
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Label Propagation Algorithm Based on Non-negative Sparse Representation
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On iterative algorithms for linear least squares problems with bound constraints
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On Theory and Practice of Row Relaxation Methods
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A survey of direct methods for sparse linear systems
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Sparse Linear Least Squares Problems in Optimization
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HPC algorithms for nonnegative decompositions
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