2018
ACL
ACL 2018
Named Entity Recognition With Parallel Recurrent Neural Networks
Abstract
AbstractWe present a new architecture for named entity recognition. Our model employs multiple independent bidirectional LSTM units across the same input and promotes diversity among them by employing an inter-model regularization term. By distributing computation across multiple smaller LSTMs we find a significant reduction in the total number of parameters. We find our architecture achieves state-of-the-art performance on the CoNLL 2003 NER dataset.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— inter-model regularization
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Deep Learning > Architectures > Neural Networks
Deep Learning > Techniques > Model Architecture
Natural Language Processing > Applications > Named Entity Recognition
Deep Learning > Learning Types > Deep Learning
Deep Learning > Architectures > Recurrent Neural Networks