Sequence to Sequence Learning with Neural Networks
[ ] 14 Dec 2014Sequence to Sequence Learningwith Neural NetworksIlya V. Neural Networks (DNNs) are powerful models that have achieved excel-lent performance on difficult Learning tasks. Although DNNswork well wheneverlarge labeled training sets are available, they cannot be used to map sequences tosequences. In this paper, we present a general end-to-end approach to sequencelearning that makes minimal assumptions on the Sequence structure. Our methoduses a multilayered Long Short-Term Memory (LSTM) to map theinput sequenceto a vector of a fixed dimensionality, and then another deep LSTM to decode thetarget Sequence from the vector.
learning that makes minimal assumptions on the sequence structure. Our method uses a multilayered Long Short-Term Memory (LSTM) to map theinput sequence to a vector of a fixed dimensionality, and then another deep LS TM to decode the target sequence from the vector. Our main result is that on an English to French
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