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Iterative Projection Methods for Structured Sparsity Regularization
In this paper we propose a general framework to characterize and solve the optimization problems underlying a large class of sparsity based regularization algorithms. More precisely, we study the minimization of learning ...
Sufficient Conditions for Uniform Stability of Regularization Algorithms
In this paper, we study the stability and generalization properties of penalized empirical-risk minimization algorithms. We propose a set of properties of the penalty term that is sufficient to ensure uniform ?-stability: ...