We will choose our universal parameter values by minimizing an estimate of their expected loss, where L train is a collection of training languages (ideally drawn IID from the distribution D of possible human languages) for which some syntactic information is available.
some other work on generalizing from source to target languages assumes the availability of source-target parallel data, or bitext.