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Workshop: OPT 2023: Optimization for Machine Learning

On the convergence of warped proximal iterations for solving nonmonotone inclusions and applications

Dimitri Papadimitriou · Bang Cong Vu


In machine learning, tackling fairness, robustness, and safeness requires to solve nonconvex optimization problems with various constraints. In this paper, we investigate the warped proximal iterations for solving the nonmonotone inclusions and its application to nonconvex QP with equality constraints.

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