Technical Reports

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UBC CS TR-2009-19 Summary

Optimization Methods for L1-Regularization, August 04, 2009 Mark Schmidt, Glenn Fung and Romer Rosales, 20 pages

In this paper we review and compare state-of-the-art optimization techniques for solving the problem of minimizing a twice-differentiable loss function subject to L1-regularization. The first part of this work outlines a variety of the approaches that are available to solve this type of problem, highlighting some of their strengths and weaknesses. In the second part, we present numerical results comparing 14 optimization strategies under various scenarios.

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