This is a simple (and parallelizable) tuning method for cdec
which is able to train the weights of very many (sparse) features.
It was used here:
  "Joint Feature Selection in Distributed Stochastic
   Learning for Large-Scale Discriminative Training in
   SMT"
(Simianer, Riezler, Dyer; ACL 2012)


Building
--------
Builds when building cdec, see ../BUILDING .
To build only parts needed for dtrain do
```
  autoreconf -ifv
  ./configure
  cd training/dtrain/; make
```

Ideas
-----
 * get approx_bleu to work?
 * implement minibatches (Minibatch and Parallelization for Online Large Margin Structured Learning)
 * learning rate 1/T?
 * use an oracle? mira-like (model vs. BLEU), feature repr. of reference!? 
 * implement lc_bleu properly
 * merge kbest lists of previous epochs (as MERT does)
 * ``walk entire regularization path''
 * rerank after each update?

Running
-------
See directories under test/ .

Legal
-----
Copyright (c) 2012-2013 by Patrick Simianer <p@simianer.de>

See the file LICENSE.txt in the root folder for the licensing terms that this software is
released under.