Gradient-Based Methods for Sparse Recovery
نویسندگان
چکیده
منابع مشابه
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, but possibly nonsmooth. It is shown that if f is convex, then the error in the objective function at iteration k is bounded by a/k for some a independent of k. Moreover, if the objective function is strongly convex, the...
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ژورنال
عنوان ژورنال: SIAM Journal on Imaging Sciences
سال: 2011
ISSN: 1936-4954
DOI: 10.1137/090775063