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Joelle Pineau | Yoshua Bengio | Aaron C. Courville | Anirudh Goyal | Dzmitry Bahdanau | Philemon Brakel | Kelvin Xu | Ryan Lowe | Yoshua Bengio | Joelle Pineau | Anirudh Goyal | Dzmitry Bahdanau | Kelvin Xu | Philemon Brakel | Ryan Lowe
[1] Thorsten Brants,et al. One billion word benchmark for measuring progress in statistical language modeling , 2013, INTERSPEECH.
[2] Andrew Y. Ng,et al. Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping , 1999, ICML.
[3] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[4] Daniel Jurafsky,et al. First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs , 2014, ArXiv.
[5] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Geoffrey J. Gordon,et al. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning , 2010, AISTATS.
[7] Richard S. Sutton,et al. Learning to predict by the methods of temporal differences , 1988, Machine Learning.
[8] Marcello Federico,et al. Report on the 10th IWSLT evaluation campaign , 2013, IWSLT.
[9] John Langford,et al. Search-based structured prediction , 2009, Machine Learning.
[10] Wojciech Zaremba,et al. Learning Simple Algorithms from Examples , 2015, ICML.
[11] Omer Levy,et al. Published as a conference paper at ICLR 2018 S IMULATING A CTION D YNAMICS WITH N EURAL P ROCESS N ETWORKS , 2018 .
[12] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[13] Franz Josef Och,et al. Minimum Error Rate Training in Statistical Machine Translation , 2003, ACL.
[14] Richard S. Sutton,et al. Temporal credit assignment in reinforcement learning , 1984 .
[15] Eduard H. Hovy,et al. Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics , 2003, NAACL.
[16] Eduardo D. Sontag,et al. Neural Networks for Control , 1993 .
[17] John Salvatier,et al. Theano: A Python framework for fast computation of mathematical expressions , 2016, ArXiv.
[18] Yishay Mansour,et al. Policy Gradient Methods for Reinforcement Learning with Function Approximation , 1999, NIPS.
[19] Ruslan Salakhutdinov,et al. Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models , 2014, ArXiv.
[20] Jason Weston,et al. A Neural Attention Model for Abstractive Sentence Summarization , 2015, EMNLP.
[21] Andreas Vlachos,et al. An investigation of imitation learning algorithms for structured prediction , 2012, EWRL.
[22] Alexander M. Rush,et al. Sequence-to-Sequence Learning as Beam-Search Optimization , 2016, EMNLP.
[23] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[24] George Kurian,et al. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation , 2016, ArXiv.
[25] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[26] Yang Liu,et al. Minimum Risk Training for Neural Machine Translation , 2015, ACL.
[27] Samy Bengio,et al. Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks , 2015, NIPS.
[28] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[29] Kuldip K. Paliwal,et al. Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..
[30] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[31] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[32] Quoc V. Le,et al. Listen, Attend and Spell , 2015, ArXiv.
[33] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[34] Daniel Marcu,et al. Learning as search optimization: approximate large margin methods for structured prediction , 2005, ICML.
[35] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[36] Richard S. Sutton,et al. Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[37] Fei-Fei Li,et al. Deep visual-semantic alignments for generating image descriptions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Trevor Darrell,et al. Long-term recurrent convolutional networks for visual recognition and description , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Yoshua Bengio,et al. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention , 2015, ICML.
[40] Tamir Hazan,et al. Direct Loss Minimization for Structured Prediction , 2010, NIPS.
[41] Marc'Aurelio Ranzato,et al. Sequence Level Training with Recurrent Neural Networks , 2015, ICLR.
[42] Ludovic Denoyer,et al. Structured prediction with reinforcement learning , 2009, Machine Learning.
[43] Yoshua Bengio,et al. Blocks and Fuel: Frameworks for deep learning , 2015, ArXiv.
[44] Yoshua Bengio,et al. Attention-Based Models for Speech Recognition , 2015, NIPS.
[45] Vaibhava Goel,et al. Minimum Bayes-risk automatic speech recognition , 2000, Comput. Speech Lang..
[46] John N. Tsitsiklis,et al. Analysis of temporal-difference learning with function approximation , 1996, NIPS 1996.
[47] Gerald Tesauro,et al. TD-Gammon, a Self-Teaching Backgammon Program, Achieves Master-Level Play , 1994, Neural Computation.
[48] Richard S. Sutton,et al. Neural networks for control , 1990 .