A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations

In Dynamic Penalization for Rank-1 SDP Relaxations (L4DC 2025, with Lavaei and Jin), we differentiate through a penalized SDP solver to learn penalty matrices that drive relaxations toward rank-1 solutions, and meta-learn initializations across tasks for faster, feasibility-preserving solves on Max-Cut and optimal power flow.