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Reporting Score Distributions Makes a Difference: Performance Study of
  LSTM-networks for Sequence Tagging

Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging

31 July 2017
Nils Reimers
Iryna Gurevych
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Papers citing "Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging"

14 / 14 papers shown
Title
Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition
Linh Le
Guido Zuccon
Gianluca Demartini
Genghong Zhao
Xia Zhang
73
1
0
07 Mar 2025
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling
  Tasks
Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks
Nils Reimers
Iryna Gurevych
39
288
0
21 Jul 2017
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Zhiwen Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
768
6,768
0
26 Sep 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
342
2,913
0
15 Sep 2016
Enriching Word Vectors with Subword Information
Enriching Word Vectors with Subword Information
Piotr Bojanowski
Edouard Grave
Armand Joulin
Tomas Mikolov
NAI
SSL
VLM
179
9,924
0
15 Jul 2016
Globally Normalized Transition-Based Neural Networks
Globally Normalized Transition-Based Neural Networks
D. Andor
Chris Alberti
David J. Weiss
Aliaksei Severyn
Alessandro Presta
Kuzman Ganchev
Slav Petrov
Michael Collins
68
568
0
19 Mar 2016
Neural Architectures for Named Entity Recognition
Neural Architectures for Named Entity Recognition
Guillaume Lample
Miguel Ballesteros
Sandeep Subramanian
Kazuya Kawakami
Chris Dyer
189
3,999
0
04 Mar 2016
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Xuezhe Ma
Eduard H. Hovy
62
2,643
0
04 Mar 2016
A Theoretically Grounded Application of Dropout in Recurrent Neural
  Networks
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks
Y. Gal
Zoubin Ghahramani
UQCV
DRL
BDL
93
1,644
0
16 Dec 2015
Bidirectional LSTM-CRF Models for Sequence Tagging
Bidirectional LSTM-CRF Models for Sequence Tagging
Zhiheng Huang
Wenyuan Xu
Kai Yu
144
3,999
0
09 Aug 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
418
149,474
0
22 Dec 2014
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
494
31,406
0
16 Jan 2013
ADADELTA: An Adaptive Learning Rate Method
ADADELTA: An Adaptive Learning Rate Method
Matthew D. Zeiler
ODL
76
6,619
0
22 Dec 2012
On the difficulty of training Recurrent Neural Networks
On the difficulty of training Recurrent Neural Networks
Razvan Pascanu
Tomas Mikolov
Yoshua Bengio
ODL
90
5,318
0
21 Nov 2012
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