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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 [--disable-gtest]
-  cd dtrain/; make
-```
-
-Running
--------
-To run this on a dev set locally:
-```
-    #define DTRAIN_LOCAL
-```
-otherwise remove that line or undef, then recompile. You need a single
-grammar file or input annotated with per-sentence grammars (psg) as you
-would use with cdec. Additionally you need to give dtrain a file with
-references (--refs) when running locally.
-
-The input for use with hadoop streaming looks like this:
-```
-    <sid>\t<source>\t<ref>\t<grammar rules separated by \t>
-```
-To convert a psg to this format you need to replace all "\n"
-by "\t". Make sure there are no tabs in your data.
-
-For an example of local usage (with the 'distributed' format)
-the see test/example/ . This expects dtrain to be built without
-DTRAIN_LOCAL.
-
-Legal
------
-Copyright (c) 2012 by Patrick Simianer <p@simianer.de>
-
-See the file ../LICENSE.txt for the licensing terms that this software is
-released under.
-