Joint Multitask Learning for Community Question AnsweringUsing Task-Specific Embeddings
Table 1: Best setting for DNNs, as found on dev.
['[EMPTY]', '[BOLD] batch', '[BOLD] dropout', '[BOLD] reg. str', '[BOLD] inter. layer', '[BOLD] task-spec. layer']
We preprocess the data using min-max scaling. We use up to 100 epochs with patience of 25, rectified linear units (ReLU) as activation functions, l2 regularization on weights, and dropout Srivastava et al.