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  4. Cited By
Learning as Search Optimization: Approximate Large Margin Methods for
  Structured Prediction

Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction

International Conference on Machine Learning (ICML), 2005
4 July 2009
Hal Daumé
D. Marcu
ArXiv (abs)PDFHTML

Papers citing "Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction"

45 / 45 papers shown
Dataset Reset Policy Optimization for RLHF
Dataset Reset Policy Optimization for RLHF
Jonathan D. Chang
Wenhao Zhan
Owen Oertell
Kianté Brantley
Dipendra Kumar Misra
Jason D. Lee
Wen Sun
OffRL
480
34
0
12 Apr 2024
Filtered Semi-Markov CRF
Filtered Semi-Markov CRFConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Urchade Zaratiana
Nadi Tomeh
Niama El Khbir
Pierre Holat
Thierry Charnois
288
1
0
29 Nov 2023
Survey of Low-Resource Machine Translation
Survey of Low-Resource Machine TranslationComputational Linguistics (CL), 2021
Barry Haddow
Rachel Bawden
Antonio Valerio Miceli Barone
Jindvrich Helcl
Alexandra Birch
AIMat
533
206
0
01 Sep 2021
A Globally Normalized Neural Model for Semantic Parsing
A Globally Normalized Neural Model for Semantic Parsing
Chenyang Huang
Wei Yang
Yanshuai Cao
Osmar Zaïane
Lili Mou
150
3
0
07 Jun 2021
Deep Policy Dynamic Programming for Vehicle Routing Problems
Deep Policy Dynamic Programming for Vehicle Routing ProblemsIntegration of AI and OR Techniques in Constraint Programming (CPAIOR), 2021
W. Kool
H. V. Hoof
J. Gromicho
Max Welling
329
153
0
23 Feb 2021
An Empirical Investigation of Beam-Aware Training in Supertagging
An Empirical Investigation of Beam-Aware Training in SupertaggingFindings (Findings), 2020
Renato M. P. Negrinho
Matthew R. Gormley
Geoffrey J. Gordon
200
3
0
10 Oct 2020
Unsupervised Text Generation by Learning from Search
Unsupervised Text Generation by Learning from SearchNeural Information Processing Systems (NeurIPS), 2020
Jingjing Li
Zichao Li
Lili Mou
Xin Jiang
Michael R. Lyu
Irwin King
212
60
0
09 Jul 2020
Learning Optimal Tree Models Under Beam Search
Learning Optimal Tree Models Under Beam Search
Jingwei Zhuo
Xinhang Li
Wei Dai
Ziru Xu
Han Li
Jian Xu
Kun Gai
223
68
0
27 Jun 2020
MLE-guided parameter search for task loss minimization in neural
  sequence modeling
MLE-guided parameter search for task loss minimization in neural sequence modeling
Sean Welleck
Dong Wang
235
9
0
04 Jun 2020
Polynomial-Time Exact MAP Inference on Discrete Models with Global
  Dependencies
Polynomial-Time Exact MAP Inference on Discrete Models with Global Dependencies
Alexander Bauer
Shinichi Nakajima
TPM
256
0
0
27 Dec 2019
Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement
  Learning
Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2019
Tahira Naseem
Abhishek Shah
Hui Wan
Radu Florian
Salim Roukos
Miguel Ballesteros
201
61
0
31 May 2019
A Fully Differentiable Beam Search Decoder
A Fully Differentiable Beam Search Decoder
R. Collobert
Awni Y. Hannun
Gabriel Synnaeve
176
43
0
16 Feb 2019
A Smoother Way to Train Structured Prediction Models
A Smoother Way to Train Structured Prediction ModelsNeural Information Processing Systems (NeurIPS), 2019
Krishna Pillutla
Vincent Roulet
Sham Kakade
Zaïd Harchaoui
193
20
0
08 Feb 2019
Learning Beam Search Policies via Imitation Learning
Learning Beam Search Policies via Imitation Learning
Renato M. P. Negrinho
Matthew R. Gormley
Geoffrey J. Gordon
247
28
0
01 Nov 2018
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation
  Algorithms
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms
Vikas Garg
Tamar Pichkhadze
137
0
0
16 Oct 2018
Optimal Completion Distillation for Sequence Learning
Optimal Completion Distillation for Sequence Learning
S. Sabour
William Chan
Mohammad Norouzi
253
45
0
02 Oct 2018
Policy Shaping and Generalized Update Equations for Semantic Parsing
  from Denotations
Policy Shaping and Generalized Update Equations for Semantic Parsing from Denotations
Dipendra Kumar Misra
Ming-Wei Chang
Xiaodong He
Anuj Kumar
OffRL
270
28
0
05 Sep 2018
Learning to Speed Up Structured Output Prediction
Learning to Speed Up Structured Output Prediction
Xingyuan Pan
Vivek Srikumar
94
7
0
11 Jun 2018
From Credit Assignment to Entropy Regularization: Two New Algorithms for
  Neural Sequence Prediction
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction
Zihang Dai
Qizhe Xie
Eduard H. Hovy
217
6
0
29 Apr 2018
Collective Entity Disambiguation with Structured Gradient Tree Boosting
Collective Entity Disambiguation with Structured Gradient Tree BoostingNorth American Chapter of the Association for Computational Linguistics (NAACL), 2018
Yi Yang
Ozan Irsoy
K. S. Rahman
367
41
0
28 Feb 2018
Structured Set Matching Networks for One-Shot Part Labeling
Structured Set Matching Networks for One-Shot Part Labeling
Jonghyun Choi
Jayant Krishnamurthy
Aniruddha Kembhavi
Ali Farhadi
297
27
0
05 Dec 2017
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in
  Knowledge Bases using Reinforcement Learning
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
Rajarshi Das
Shehzaad Dhuliawala
Manzil Zaheer
Luke Vilnis
Ishan Durugkar
A. Krishnamurthy
Alex Smola
Andrew McCallum
KELM
488
576
0
15 Nov 2017
A Continuous Relaxation of Beam Search for End-to-end Training of Neural
  Sequence Models
A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models
Kartik Goyal
Graham Neubig
Chris Dyer
Taylor Berg-Kirkpatrick
3DV
326
41
0
01 Aug 2017
SEARNN: Training RNNs with Global-Local Losses
SEARNN: Training RNNs with Global-Local LossesInternational Conference on Learning Representations (ICLR), 2017
Rémi Leblond
Jean-Baptiste Alayrac
A. Osokin
Damien Scieur
254
53
0
14 Jun 2017
Fast and Accurate Neural Word Segmentation for Chinese
Fast and Accurate Neural Word Segmentation for Chinese
Deng Cai
Zhao Hai
Zhisong Zhang
Yuan Xin
Yongjian Wu
Feiyue Huang
VLM
106
94
0
24 Apr 2017
Differentiable Scheduled Sampling for Credit Assignment
Differentiable Scheduled Sampling for Credit Assignment
Kartik Goyal
Chris Dyer
Taylor Berg-Kirkpatrick
211
40
0
23 Apr 2017
An Actor-Critic Algorithm for Sequence Prediction
An Actor-Critic Algorithm for Sequence Prediction
Dzmitry Bahdanau
Philemon Brakel
Kelvin Xu
Anirudh Goyal
Ryan J. Lowe
Joelle Pineau
Aaron Courville
Yoshua Bengio
326
663
0
24 Jul 2016
Imitation Learning with Recurrent Neural Networks
Imitation Learning with Recurrent Neural Networks
Khanh Nguyen
143
10
0
18 Jul 2016
Global Neural CCG Parsing with Optimality Guarantees
Global Neural CCG Parsing with Optimality GuaranteesConference on Empirical Methods in Natural Language Processing (EMNLP), 2016
Kenton Lee
M. Lewis
Luke Zettlemoyer
222
41
0
05 Jul 2016
Sequence-to-Sequence Learning as Beam-Search Optimization
Sequence-to-Sequence Learning as Beam-Search OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP), 2016
Sam Wiseman
Alexander M. Rush
384
614
0
09 Jun 2016
Training with Exploration Improves a Greedy Stack-LSTM Parser
Training with Exploration Improves a Greedy Stack-LSTM Parser
Miguel Ballesteros
Yoav Goldberg
Chris Dyer
Noah A. Smith
213
78
0
11 Mar 2016
The Structured Weighted Violations Perceptron Algorithm
The Structured Weighted Violations Perceptron Algorithm
Rotem Dror
Roi Reichart
DRL
200
1
0
09 Feb 2016
Parser for Abstract Meaning Representation using Learning to Search
Parser for Abstract Meaning Representation using Learning to Search
Sudha Rao
Yogarshi Vyas
Hal Daumé
Philip Resnik
202
13
0
26 Oct 2015
Learning to Search for Dependencies
Learning to Search for Dependencies
Kai-Wei Chang
He He
Hal Daumé
John Langford
264
19
0
18 Mar 2015
Learning Reductions that Really Work
Learning Reductions that Really Work
A. Beygelzimer
Hal Daumé
John Langford
Paul Mineiro
AI4CE
248
25
0
09 Feb 2015
Learning to Search Better Than Your Teacher
Learning to Search Better Than Your Teacher
Kai-Wei Chang
A. Krishnamurthy
Alekh Agarwal
Hal Daumé
John Langford
OffRL
251
233
0
08 Feb 2015
Learning Structured Outputs from Partial Labels using Forest Ensemble
Learning Structured Outputs from Partial Labels using Forest Ensemble
T. Tran
Dinh Q. Phung
Svetha Venkatesh
136
1
0
24 Jul 2014
A Credit Assignment Compiler for Joint Prediction
A Credit Assignment Compiler for Joint PredictionNeural Information Processing Systems (NeurIPS), 2014
Kai-Wei Chang
He He
Hal Daumé
John Langford
Stéphane Ross
411
20
0
07 Jun 2014
Latent Structured Ranking
Latent Structured RankingConference on Uncertainty in Artificial Intelligence (UAI), 2012
Jason Weston
John Blitzer
BDL
203
12
0
16 Oct 2012
Understanding Exhaustive Pattern Learning
Understanding Exhaustive Pattern Learning
Libin Shen
244
3
0
20 Apr 2011
An Introduction to Conditional Random Fields
An Introduction to Conditional Random Fields
Charles Sutton
Andrew McCallum
AI4CEBDLCMLTPM
303
1,266
0
17 Nov 2010
Learning to Predict Combinatorial Structures
Learning to Predict Combinatorial Structures
Shankar Vembu
237
4
0
22 Dec 2009
A Large-Scale Exploration of Effective Global Features for a Joint
  Entity Detection and Tracking Model
A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking ModelHuman Language Technology - The Baltic Perspectiv (LTBP), 2005
Hal Daumé
D. Marcu
398
106
0
04 Jul 2009
Search-based Structured Prediction
Search-based Structured PredictionMachine-mediated learning (ML), 2009
Hal Daumé
John Langford
Daniel Marcu
GNN
409
595
0
04 Jul 2009
Cross-Task Knowledge-Constrained Self Training
Cross-Task Knowledge-Constrained Self TrainingConference on Empirical Methods in Natural Language Processing (EMNLP), 2008
Hal Daumé
CLL
200
26
0
04 Jul 2009
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