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Deep Learning for NLP (without Magic).

, and . HLT-NAACL, page 1-3. The Association for Computational Linguistics, (2013)

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Combining Heterogeneous Classifiers for Word-Sense Disambiguation., , , , and . SENSEVAL@ACL, page 87-90. Association for Computational Linguistics, (2001)Learning a Product of Experts with Elitist Lasso., and . IJCNLP, page 525-533. Asian Federation of Natural Language Processing / ACL, (2013)Machine Translation Evaluation with Textual Entailment Features., , , and . WMT@EACL, page 37-41. Association for Computational Linguistics, (2009)Feature-Rich Phrase-based Translation: Stanford University's Submission to the WMT 2013 Translation Task., , , , , , , , and . WMT@ACL, page 148-153. The Association for Computer Linguistics, (2013)Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions., , , , and . EMNLP, page 151-161. ACL, (2011)Tree-Structured Composition in Neural Networks without Tree-Structured Architectures., , and . CoCo@NIPS, volume 1583 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Learning by Abstraction: The Neural State Machine., and . NeurIPS, page 5901-5914. (2019)Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines., , and . EMNLP, page 618-626. ACL, (2006)Language Learning: Beyond Thunderdome.. CoNLL, page 138. ACL, (2004)The segmentation problem in morphology learning.. CoNLL, page 299-306. ACL, (1998)