Poster
in
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
Abstract:
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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