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2013 NeurIPS NeurIPS 2013

On Decomposing the Proximal Map

The proximal map is the key step in gradient-type algorithms, which have become prevalent in large-scale high-dimensional problems. For simple functions this proximal map is available in closed-form while for more complicated functions it can become highly nontrivial. Motivated by the need of combining regularizers to simultaneously induce different types of structures, this paper initiates a systematic investigation of when the proximal map of a sum of functions decomposes into the composition of the proximal maps of the individual summands. We not only unify a few known results scattered in the literature but also discover several new decompositions obtained almost effortlessly from our theory.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Mathematics & Optimization
📈 Trend Setter - Regularization
🐣 Hot Topic Early Bird - optimization algorithm

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