A Dual Active-set Quadratic Programming Method for Finding Sparse Least-squares Solutions
نویسندگان
چکیده
Many imaging and compressed sensing applications seek sparse solutions to large under-determined least-squares problems. The basis pursuit (BP) approach minimizes the 1-norm of the solution, and the BP denoising (BPDN) approach balances it against the least-squares fit. The duals of these problems are conventional linear and quadratic programs. We introduce a modified parameterization of the BPDN problem and explore the effectiveness of active-set methods for solving its dual. Our algorithm for solving a generalized form of the BP dual unifies several existing algorithms and is applicable to large-scale examples.
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تاریخ انتشار 2012