Stochastic Lagrangian-based method for nonconvex optimization with nonlinear constraints
Dimitri Papadimitriou,
Bang Vu
Abstract:The Augmented Lagrangian Method (ALM) is one of the most common approaches for solving linear and nonlinear constrained problems. However, for nonconvex objectives, the handling of nonlinear inequality constraints remains challenging. In this paper, we propose a stochastic ALM with Backtracking Line Search that performs on a subset (mini-batch) of randomly selected points for the solving of nonconvex problems. The considered class of problems include both nonlinear equality and inequality constraints. Together… Show more
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