Training parsers by inverse reinforcement learning
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[1] E. Jaynes. Information Theory and Statistical Mechanics , 1957 .
[2] Donald Geman,et al. Application of the Gibbs distribution to image segmentation , 1984, ICASSP.
[3] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[4] Yoav Freund,et al. Large Margin Classification Using the Perceptron Algorithm , 1998, COLT' 98.
[5] E. Yaz. Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.
[6] E Rivas,et al. A dynamic programming algorithm for RNA structure prediction including pseudoknots. , 1998, Journal of molecular biology.
[7] Andrew Y. Ng,et al. Pharmacokinetics of a novel formulation of ivermectin after administration to goats , 2000, ICML.
[8] Christian Igel,et al. Improving the Rprop Learning Algorithm , 2000 .
[9] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[10] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[11] Hinrich Schütze,et al. Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.
[12] Michael Collins,et al. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms , 2002, EMNLP.
[13] Michael Collins,et al. Head-Driven Statistical Models for Natural Language Parsing , 2003, CL.
[14] Mark Steedman,et al. Example Selection for Bootstrapping Statistical Parsers , 2003, NAACL.
[15] Dan Klein,et al. A* Parsing: Fast Exact Viterbi Parse Selection , 2003, NAACL.
[16] Pat Langley,et al. Editorial: On Machine Learning , 1986, Machine Learning.
[17] Ben Taskar,et al. Max-Margin Parsing , 2004, EMNLP.
[18] Brian Roark,et al. Incremental Parsing with the Perceptron Algorithm , 2004, ACL.
[19] Ben Taskar,et al. Exponentiated Gradient Algorithms for Large-margin Structured Classification , 2004, NIPS.
[20] Pieter Abbeel,et al. Apprenticeship learning via inverse reinforcement learning , 2004, ICML.
[21] Eugene Charniak,et al. Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking , 2005, ACL.
[22] Frank Keller,et al. Lexicalization in Crosslinguistic Probabilistic Parsing: The Case of French , 2005, ACL.
[23] Michael Collins,et al. Discriminative Reranking for Natural Language Parsing , 2000, CL.
[24] Ben Taskar,et al. Learning structured prediction models: a large margin approach , 2005, ICML.
[25] J. Andrew Bagnell,et al. Maximum margin planning , 2006, ICML.
[26] William W. Cohen,et al. Single-pass online learning: performance, voting schemes and online feature selection , 2006, KDD '06.
[27] Gábor Lugosi,et al. Prediction, learning, and games , 2006 .
[28] I. Dan Melamed,et al. Advances in Discriminative Parsing , 2006, ACL.
[29] Daniel Marcu,et al. Practical structured learning techniques for natural language processing , 2006 .
[30] Thomas Hofmann,et al. Predicting Structured Data (Neural Information Processing) , 2007 .
[31] Ivan Titov,et al. Constituent Parsing with Incremental Sigmoid Belief Networks , 2007, ACL.
[32] Nathan Ratliff,et al. Online) Subgradient Methods for Structured Prediction , 2007 .
[33] Robert E. Schapire,et al. A Game-Theoretic Approach to Apprenticeship Learning , 2007, NIPS.
[34] Nathan D. Ratliff. Subgradient Methods for Structured Prediction , 2007 .
[35] Csaba Szepesvári,et al. Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods , 2007, UAI.
[36] Ludovic Denoyer,et al. Sequence Labeling with Reinforcement Learning and Ranking Algorithms , 2007, ECML.
[37] Dan Klein,et al. Learning and Inference for Hierarchically Split PCFGs , 2007, AAAI.
[38] Xavier Carreras,et al. Exponentiated gradient algorithms for log-linear structured prediction , 2007, ICML '07.
[39] Anind K. Dey,et al. Maximum Entropy Inverse Reinforcement Learning , 2008, AAAI.
[40] Christopher D. Manning,et al. Efficient, Feature-based, Conditional Random Field Parsing , 2008, ACL.
[41] Yoram Singer,et al. Pegasos: primal estimated sub-gradient solver for SVM , 2011, Math. Program..