Use model's run_time to determine training speed during toHTML in multi-node
operation.  This prevents the displayed training speed from dropping in-between
model updates (time advances but #training samples doesn't).
Cosmetics: Refactor code for ADADELTA for bias.
Apply L1/L2 penalty to bias values as well.
Update DL R Vignette wrt input dropout and L1/L2 penalty.
Change default values for ADADELTA hyperparameters to 1e-8/0.99.
Change default activation function to Rectifier.
Use Rectifier without Dropout for DL_imbalance_large RUnit test.
Merge branch 'master' of https://github.com/0xdata/h2o