mloss | Projects authored by andreas krause.

Matlab toolbox for submodular function optimization 2.0

by krausea - April 7, 2010, 09:53:40 CET [ ] 32563 views, 9177 downloads, 0 subscriptions

About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others.

Changes:

Modified specification of optional parameters (using sfo_opt)
Added sfo_ls_lazy for maximizing nonnegative submodular functions
Added sfo_fn_infogain, sfo_fn_lincomb, sfo_fn_invert, ...
Added additional documentation and more examples
Now Octave ready

Authors: Andreas Krause
License: Bsd
Programming Language: Matlab, Octave

Operating System: Linux, Macosx, Windows
Data Formats: Matlab, Octave
JMLR-MLOSS Publication: JMLR Page
Tags: Matlab, Active Learning, Optimization, Markov Random Fields, Experimental Design, Submodularity

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Matlab toolbox for submodular function optimization 2.0