dOPT: Differentiating Conic Optimization via Geometric Reduction
dOPT creates a solver-agnostic method to differentiate conic optimization problems by transforming them into an equality-constrained quadratic program. This reduction allows efficient gradient computation using a single linear solve, independent of the original solver. It captures local geometry and handles singular configurations better than existing methods, leading to faster backward passes.