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Learning to Search for Dependencies
v1v2 (latest)

Learning to Search for Dependencies

18 March 2015
Kai-Wei Chang
He He
Hal Daumé
John Langford
ArXiv (abs)PDFHTML

Papers citing "Learning to Search for Dependencies"

8 / 8 papers shown
Mitigating Covariate Shift in Imitation Learning via Offline Data
  Without Great Coverage
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage
Jonathan D. Chang
Masatoshi Uehara
Dhruv Sreenivas
Rahul Kidambi
Wen Sun
OffRL
382
37
0
06 Jun 2021
A Neural Entity Coreference Resolution Review
A Neural Entity Coreference Resolution ReviewExpert systems with applications (ESWA), 2019
Nikolaos Stylianou
I. Vlahavas
370
43
0
21 Oct 2019
Provably Efficient Imitation Learning from Observation Alone
Provably Efficient Imitation Learning from Observation AloneInternational Conference on Machine Learning (ICML), 2019
Wen Sun
Anirudh Vemula
Byron Boots
J. Andrew Bagnell
440
111
0
27 May 2019
BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement
  Learning
BOOK: Storing Algorithm-Invariant Episodes for Deep Reinforcement Learning
Simyung Chang
Y. Yoo
Jaeseok Choi
Nojun Kwak
OffRL
252
1
0
05 Sep 2017
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task
Amr Sharaf
Shi Feng
Khanh Nguyen
Kianté Brantley
Hal Daumé
175
4
0
03 Aug 2017
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential
  Prediction
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun
Arun Venkatraman
Geoffrey J. Gordon
Byron Boots
J. Andrew Bagnell
404
245
0
03 Mar 2017
Improving Coreference Resolution by Learning Entity-Level Distributed
  Representations
Improving Coreference Resolution by Learning Entity-Level Distributed RepresentationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2016
Kevin Clark
Christopher D. Manning
324
347
0
04 Jun 2016
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
436
20
0
07 Jun 2014
1
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