SMIDAShttp://mloss.orgUpdates and additions to SMIDASenSun, 15 Aug 2010 18:51:51 -0000SMIDAS 1.1<html><p>SMIDAS is a C++ implementation of the stochastic mirror descent algorithm proposed in </p> <pre><code>* Shai Shalev-Shwartz and Ambuj Tewari, Stochastic methods for l1 regularized loss minimization. Proceedings of the 26th International Conference on Machine Learning, pages 929-936, 2009. </code></pre><p>It can be used for l1-regularized loss minimization for both classification and regression problems. </p> <p>Currently supported loss functions are the logistic loss, the hinge loss, and the squared loss [L(a,b) = (a-b)2]. SMIDAS is designed to run fast even for high-dimensional large datasets and can exploit the sparsity in the examples. </p></html>Shai Shalev Shwartz, Ambuj TewariSun, 15 Aug 2010 18:51:51 -0000 regularizationlarge datasetsmirror descentsparsity