On Global Linear Convergence in Stochastic Nonconvex Optimization for Semidefinite Programming
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DOI: 10.1109/tsp.2019.2925609
Abstract: Nonconvex reformulations via low-rank factorization for stochastic convex semidefinite optimization problem have attracted arising attention due to their empirical efficiency and scalability. Compared with the original convex formulations, the nonconvex ones typically involve much fewer… read more here.
Keywords: global linear; optimization; linear convergence; convergence stochastic ... See more keywords