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DIFFERENTIABLE PROGRAMMING A LA MOREAU

Vincent Roulet,Zaid Harchaoui

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)（2022）

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Abstract
The notion of a Moreau envelope is central to the analysis of first-order optimization algorithms for machine learning and signal processing. We define a compositional calculus adapted to Moreau envelopes and show how to apply it to deep networks, and, more broadly, to learning systems equipped with automatic differentiation and implemented in the spirit of differentiable programming.
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Key words
Moreau envelope,differentiable programming,mathematical optimization,deep learning
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