Parallel Stochastic Optimization Framework for Large-Scale Non-Convex Stochastic Problems
Naeimeh Omidvar,
An Liu,
Vincent Lau
et al.
Abstract:In this paper, we consider the problem of stochastic optimization, where the objective function is in terms of the expectation of a (possibly non-convex) cost function that is parametrized by a random variable. While the convergence speed is critical for many emerging applications, most existing stochastic optimization methods suffer from slow convergence. Furthermore, the emerging technology of parallel computing has motivated an increasing demand for designing new stochastic optimization schemes that can han… Show more
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