Optimization Methods for L1-Regularization

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Authors Mark Schmidt, Glenn Fung, Romer Rosaless
Journal/Conference Name UBC Technical Report,
Paper Category
Paper Abstract 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 `1-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.
Date of publication 2009
Code Programming Language MATLAB
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