Statistical Learning
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Improving Decision Sparsity
Neural Information Processing Systems
Sparsity is a central aspect of interpretability in machine learning.
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Mirror and Preconditioned Gradient Descent in Wasserstein Space
Neural Information Processing Systems
In particular, its convergence guarantees can be obtained under relative smoothness and convexity of the Fenchel transform of the potential, with respect to the objective.
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