M
Michael A. Saunders
Researcher at Stanford University
Publications - 200
Citations - 37808
Michael A. Saunders is an academic researcher from Stanford University. The author has contributed to research in topics: Nonlinear programming & Constrained optimization. The author has an hindex of 59, co-authored 194 publications receiving 34804 citations. Previous affiliations of Michael A. Saunders include Carleton University & University of California, San Diego.
Papers
More filters
Journal ArticleDOI
Atomic Decomposition by Basis Pursuit
TL;DR: Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having the smallest l1 norm of coefficients among all such decompositions.
Journal ArticleDOI
Atomic Decomposition by Basis Pursuit
TL;DR: This work gives examples exhibiting several advantages over MOF, MP, and BOB, including better sparsity and superresolution, and obtains reasonable success with a primal-dual logarithmic barrier method and conjugate-gradient solver.
Journal ArticleDOI
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
TL;DR: Numerical tests are described comparing I~QR with several other conjugate-gradient algorithms, indicating that I ~QR is the most reliable algorithm when A is ill-conditioned.
Journal ArticleDOI
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
TL;DR: An SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility in the original problem and the QP subproblems is discussed.
Journal ArticleDOI
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
TL;DR: An SQP algorithm that uses a smooth augmented Lagrangian merit function and makes explicit provision for infeasibility in the original problem and the QP subproblems is discussed and a reduced-Hessian semidefinite QP solver (SQOPT) is discussed.