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cs.DS2017★ 1 cited
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
Aleksander Mądry, Slobodan Mitrović, Ludwig Schmidt
Sparsity-based methods are widely used in machine learning, statistics, and signal processing. There is now a rich class of structured sparsity approaches that expand the modeling…
cs.LG2017★ 1 cited
Graph-Sparse Logistic Regression
Alexander LeNail, Ludwig Schmidt, Johnathan Li +4
We introduce Graph-Sparse Logistic Regression, a new algorithm for classification for the case in which the support should be sparse but connected on a graph. We val- idate this al…