“∇-Prox: Differentiable Proximal Algorithm Modeling for Large-scale Optimization” by Lai, Wei, Fu, Härtel and Heide
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Title:
- ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-scale Optimization
Session/Category Title: Surfaces, Strips, Lights
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Abstract:
∇-Prox is a domain-specific language and compiler for large-scale optimization that transforms optimization problems into differentiable proximal solvers. With a few lines of code, ∇-Prox makes it easier to prototype different learning-based, bi-level optimization algorithms based on user requirements with regard to memory constraints or training budget for a diverse range of applications.
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