Parallel Selective Algorithms for Nonconvex Big Data Optimization
نویسندگان
چکیده
منابع مشابه
Hybrid Random/Deterministic Parallel Algorithms for Nonconvex Big Data Optimization
We propose a decomposition framework for the parallel optimization of the sum of a differentiable (possibly nonconvex) function and a nonsmooth (possibly nonseparable), convex one. The latter term is usually employed to enforce structure in the solution, typically sparsity. The main contribution of this work is a novel parallel, hybrid random/deterministic decomposition scheme wherein, at each ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2015
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2015.2399858