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Fast and Adaptive Online Training of Feature-Rich Translation Models Spence Green, Sida Wang, Daniel Cer, and Christopher D. Manning Computer Science Department, Stanford University {spenceg,sidaw,danielcer,manning}@stan
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Document Date: 2013-08-07 08:12:24

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IBM / Penn Arabic Treebank / MIT Press / Penn Chinese Treebank / 3M / Arabic Treebank / NIST / ICANN / Penn Treebank / /

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United States / /

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Carnegie Mellon University / Stanford University / Language Technologies Institute / store Gt / /

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NaturalFeature

MT. MIRA Chiang et al. / Arabic-English mountain / MT. AROW / MT AdaGrad / MT. MIRA / Chinese-English mountain / /

Organization

Defense Advanced Research Projects Agency / National Science Foundation / MIT / US government / Christopher D. Manning Computer Science Department / Language Technologies Institute / Stanford University / Carnegie Mellon University / /

Person

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Position

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Product

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Montana / /

PublishedMedium

Machine Learning / /

SportsLeague

Stanford University / /

Technology

2 Adaptive Online Algorithms / line search algorithm / 3 Adaptive Online MT Algorithm / machine translation / 3.1 Pairwise Logistic Loss Function Algorithm / Prior Online Algorithms / machine learning / shared memory / tuning algorithm / Recent discriminative algorithms / natural language processing / Java / Online passive-aggressive algorithms / 3.3 Parallelization Algorithm / adaptive algorithm / /

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