lisa-lab/pylearn — pull request #26 by dwf (2011-11-03 19:52:27+00:00)
Title: New implementation of feature sign search

This replaces the blind MATLAB translation of Honglak Lee's feature sign search code for L1-penalized quadratic minimization, with an independent implementation written entirely by me *without* reference to his code (except to test solutions against).

I wrote this mainly so I could understand the algorithm better, how to speed it up, and how to apply it to things that aren't strictly linear (this implementation only covers the quadratic, linear case, but it should be extensible at least to general convex functions, perhaps to non-convex functions without the same guarantees on convergence).

More importantly, perhaps, the previous code in featuresign.py was *unsuitable* for inclusion in pylearn2 as it was very clearly a derivative work of Honglak's copyrighted code. With no clear license attached to Honglak's code and without his explicit permission, we can't relicense a derivative work for inclusion in our package, subject to a single set of license terms. This reimplementation is a completely separate work produced by reading the paper only, and is thus free of any intellectual property concerns.

The tests include solutions produced by my previous Honglak translation, in order to compare for equality (up to numerical noise).