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Found 3 papers, 1 papers with code
Learning Variational Models with Unrolling and Bilevel Optimization
In this paper we consider the problem of learning variational models in the context of supervised learning via risk minimization.
Primal-dual residual networks
In this work, we propose a deep neural network architecture motivated by primal-dual splitting methods from convex optimization.
A Sinkhorn-Newton method for entropic optimal transport
We further investigate numerically the robustness of the proposed method with respect to parameters such as the mesh size of the discretization.
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