support for different layer size (but it is currently broken for ITG)
implemented ITG autoencoder
added classification cost in searching for a derivation
bugfix for updating parameters
clip the learning rate
dump only the required entries
removed unused layer
revised hardhan and hinge
bugfix for adagrad in online learner + better nn learning
updated to read data in parallel (TODO: mpi version by splitting out shared codes)
implemented our own neural network ngram lm
implemented sample program... Currently, we compute perplexity but nn lm return "unnormalized log-orobabilities" which is not correct!