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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.
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