The Toolkit for Advanced Discriminative Modeling (TADM) is a C++ implementation for estimating the parameters of discriminative models, such as maximum entropy models. It uses the PETSc and TAO toolkits to provide high performance and scalability. TADM is a rebranding and relicensing of a system written by Rob Malouf and distributed previously as "estimate". A paper describing the use of the original system for evaluating various algorithms for training maximum entropy models is available here: http://bulba.sdsu.edu/~malouf/papers/conll02.pdf TADM currently has very little documentation, so it can be rough for first time users to work out how to use it. Look in the docs directory for a start and try using the python scripts, which handle a lot of low-level details and accept some well-known formats for stating features. See docs/install.txt for instructions on compiling and installing TADM on your machine. See the data directory for two example data sets formatted to work with the Python front end and instructions for testing them. If you need help, please post a message to the TADM sourceforge help forum: http://sourceforge.net/forum/forum.php?forum_id=473054 Asking questions on the forum is much preferable to contacting the developers directly so that everyone can benefit from the answers which are provided. A lot of useful information regarding maximum entropy modeling and software is available on Zhang Le's maxent page: http://homepages.inf.ed.ac.uk/s0450736/maxent.html Finally, Jason Baldridge has used TADM in his Computational Linguistics II class at the University of Texas at Austin. Homework 3 from the Fall 2006 version of the class is likely to be quite useful for people who would like something like a tutorial for using TADM. You can download it from the following location: http://comp.ling.utexas.edu/jbaldrid/courses/2006/cl2/cl2-hw3.tgz