further aggressive parallelization
better parallelization and added iostream interface for gradient (TODO: write similar things for Model)
forked the implementation into impl.hpp
implemented recurrent neural network ngram LM with NCE
bugfix for recurrent LM
removed epsilon, since we do not use it
renamed to rnn_sentence, since we do not compute ngram-wise scoring
implemented a variant of recurrent ngram LM (or we may call this limited-memory recurrent ngram lm)
bugfix for bi initialization
added limited-memory recurrent ngram lm
revise the bc to keep only required part
faster score computation
tweaked debug messages
renamed the name of the initial variables
added normalized version, and use it to compute log-likelihood and perplexity
renamed recurrent network to rnn and implemented non-recurrent version (but not tested)