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Distributional Representations for Handling Sparsity in Supervised Sequence-Labeling
Fei Huang
|
Alexander Yates
|
Paper Details:
Month: August
Year: 2009
Location: Suntec, Singapore
Venue:
ACL |
IJCNLP |
Citations
URL
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
Amarnag Subramanya
|
Slav Petrov
|
Fernando Pereira
|
The Necessity of Combining Adaptation Methods
Ming-Wei Chang
|
Michael Connor
|
Dan Roth
|
Linking Named Entities to Any Database
Avirup Sil
|
Ernest Cronin
|
Penghai Nie
|
Yinfei Yang
|
Ana-Maria Popescu
|
Alexander Yates
|
Biased Representation Learning for Domain Adaptation
Fei Huang
|
Alexander Yates
|
Revisiting Embedding Features for Simple Semi-supervised Learning
Jiang Guo
|
Wanxiang Che
|
Haifeng Wang
|
Ting Liu
|
Neural Networks Leverage Corpus-wide Information for Part-of-speech Tagging
Yuta Tsuboi
|
Word Embeddings through Hellinger PCA
Rémi Lebret
|
Ronan Collobert
|
Learning Representations for Weakly Supervised Natural Language Processing Tasks
Fei Huang
|
Arun Ahuja
|
Doug Downey
|
Yi Yang
|
Yuhong Guo
|
Alexander Yates
|
Big Data Small Data, In Domain Out-of Domain, Known Word Unknown Word: The Impact of Word Representations on Sequence Labelling Tasks
Lizhen Qu
|
Gabriela Ferraro
|
Liyuan Zhou
|
Weiwei Hou
|
Nathan Schneider
|
Timothy Baldwin
|
Graph-Based Lexicon Expansion with Sparsity-Inducing Penalties
Dipanjan Das
|
Noah A. Smith
|
Focused training sets to reduce noise in NER feature models
Amber McKenzie
|
Compound Embedding Features for Semi-supervised Learning
Mo Yu
|
Tiejun Zhao
|
Daxiang Dong
|
Hao Tian
|
Dianhai Yu
|
Overcoming the Memory Bottleneck in Distributed Training of Latent Variable Models of Text
Yi Yang
|
Alexander Yates
|
Doug Downey
|
Word Representations: A Simple and General Method for Semi-Supervised Learning
Joseph Turian
|
Lev-Arie Ratinov
|
Yoshua Bengio
|
Open-Domain Semantic Role Labeling by Modeling Word Spans
Fei Huang
|
Alexander Yates
|
Domain Adaptation by Constraining Inter-Domain Variability of Latent Feature Representation
Ivan Titov
|
Learning to Predict Distributions of Words Across Domains
Danushka Bollegala
|
David Weir
|
John Carroll
|
Fast Easy Unsupervised Domain Adaptation with Marginalized Structured Dropout
Yi Yang
|
Jacob Eisenstein
|
Learning Hidden Markov Models with Distributed State Representations for Domain Adaptation
Min Xiao
|
Yuhong Guo
|
FLORS: Fast and Simple Domain Adaptation for Part-of-Speech Tagging
Tobias Schnabel
|
Hinrich Schütze
|
Clinical Information Extraction Using Word Representations
Shervin Malmasi
|
Hamed Hassanzadeh
|
Mark Dras
|
Exploring Representation-Learning Approaches to Domain Adaptation
Fei Huang
|
Alexander Yates
|
Language Models as Representations for Weakly Supervised NLP Tasks
Fei Huang
|
Alexander Yates
|
Arun Ahuja
|
Doug Downey
|
Adapting Text instead of the Model: An Open Domain Approach
Gourab Kundu
|
Dan Roth
|
Scoring Spoken Responses Based on Content Accuracy
Fei Huang
|
Lei Chen
|
Jana Sukkarieh
|
Word Embeddings vs Word Types for Sequence Labeling: the Curious Case of CV Parsing
Melanie Tosik
|
Carsten Lygteskov Hansen
|
Gerard Goossen
|
Mihai Rotaru
|
A critique of word similarity as a method for evaluating distributional semantic models
Miroslav Batchkarov
|
Thomas Kober
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Jeremy Reffin
|
Julie Weeds
|
David Weir
|
Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction
Joël Legrand
|
Yannick Toussaint
|
Chedy Raïssi
|
Adrien Coulet
|
http://sourceforge.net/projects/crf/
http://bioie.ldc.upenn.edu/
Field Of Study
Task
Tagging
Chunking
Biomedical
Approach
Structured Prediction
Language
English
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