mloss.org DALhttp://mloss.orgUpdates and additions to DALenTue, 18 Feb 2014 19:07:06 -0000DAL 1.1http://mloss.org/software/view/183/<html><ul>
<li><p>DAL is an efficient and flexibible MATLAB toolbox for solving the following optimization problem:
</p>
<pre><code>minimize f(Ax) + lambda*c(x)
</code></pre><p>where A (m x n) is a design matrix, f is a loss function, and c is a measure of sparsity.
</p>
</li>
<li><p>DAL can handle your favorite (convex, smooth) loss functions (squared loss, logistic loss, etc).
</p>
</li>
<li><p>DAL can handle A (and its transpose) provided as function handles.
</p>
</li>
<li><p>DAL can handle several "sparsity" measures in an unified way. Currently L1, grouped L1, and trace norm (testing, requires PROPACK) measures are supported.
</p>
</li>
<li><p>DAL is efficient when m<<n (m: #samples, n: #unknowns) or the matrix A is poorly conditioned.
</p>
</li>
<li><p>DAL is fast when the solution is sparse but the matrix A can be dense.
</p>
</li>
<li><p>DAL is written in MATLAB.
</p>
</li>
</ul></html>Ryota TomiokaTue, 18 Feb 2014 19:07:06 -0000http://mloss.org/software/rss/comments/183http://mloss.org/software/view/183/optimizationtrace normgroup lassolassosparse learningl1 regularizationlogistic regression