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Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error States
Ashish Vaswani
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Kenji Sagae
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Paper Details:
Year: 2016
Venue:
TACL |
Citations
URL
Training with Exploration Improves a Greedy Stack LSTM Parser
Miguel Ballesteros
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Yoav Goldberg
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Chris Dyer
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Noah A. Smith
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Fast(er) Exact Decoding and Global Training for Transition-Based Dependency Parsing via a Minimal Feature Set
Tianze Shi
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Liang Huang
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Lillian Lee
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Valency-Augmented Dependency Parsing
Tianze Shi
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Lillian Lee
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Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks
Wenduan Xu
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Michael Auli
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Stephen Clark
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Globally Normalized Transition-Based Neural Networks
Daniel Andor
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Chris Alberti
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David Weiss
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Aliaksei Severyn
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Alessandro Presta
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Kuzman Ganchev
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Slav Petrov
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Michael Collins
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http://nlg.isi.edu/software/nplm/
http://www.logos.ic.i.u-tokyo
http://github.com/sagae/nndep
Field Of Study
Linguistic Trends
Embeddings
Task
Tagging
Approach
Structured Prediction
Language
English
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