Google proposes efficient and modular Implicit Differentiation for Optimization Problems

A new Google Research study has proposed a unified, efficient and modular approach for implicit differentiation of optimization problems that combines the benefits of implicit differentiation and automatic differentiation (autodiff). The researchers say solvers equipped with implicit differentiation set up by the proposed framework can make the autodiff process more efficient for end-users.

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