Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks

Recent papers have shown that neural networks obtain state-of-the-art performance on several different sequence tagging tasks. One appealing property of such systems is their generality, as excellent performance can be achieved with a unified architecture and without task-specific feature engineerin...

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Bibliographische Detailangaben

Hauptverfasser:	Yang, Zhilin, Salakhutdinov, Ruslan, Cohen, William W
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language Computer Science - Learning
Online-Zugang:	Volltext bestellen
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