discriminative reranking
Low Dimensional Discriminative Reranking
... In this paper, we proposed a novel family of mod- els for discriminative reranking problem and showed improvements for the POS tagging task in four dif- ferent languages. Here, we restricted our scope to ...
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Discriminative Reranking for Machine Translation
... Discriminative reranking allows us to use global features which are unavailable for the baseline ...tasks. Reranking enables rapid experimentation with complex feature functions, because the complex ...
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Adapting Discriminative Reranking to Grounded Language Learning
... model, discriminative reranking (Collins, 2000) could po- tentially improve its ...a discriminative classifier that uses global features of complete parses to identify correct interpreta- tions, a ...
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Hidden Variable Models for Discriminative Reranking
... reranking model. Typically, each candidate struc- ture (e.g., each parse tree in the case of parsing) is mapped to a feature–vector representation. Previous work has generally relied on two approaches to rep- ...
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Discriminative Reranking for Grammatical Error Correction with Statistical Machine Translation
... a discriminative reranking algo- rithm using perceptron which successfully exploits syntactic features for N-best reranking for common translation tasks (Carter and Monz, ...
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Discriminative Reranking for Semantic Parsing
... tive reranking, which explores arbitrary global ...gate discriminative reranking upon a base- line semantic parser, S CISSOR , where the composition of meaning representations is guided by ...that ...
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Mandarin Part of Speech Tagging and Discriminative Reranking
... 1998) discriminative reranking approach that was originally developed by Collins and Koo (2005) for ...The reranking algorithm takes as input a list of candidates produced by some probabilistic ...
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Coarse to Fine n Best Parsing and MaxEnt Discriminative Reranking
... Discriminative reranking is one method for constructing high-performance statis- tical parsers (Collins, 2000). A discrim- inative reranker requires a source of can- didate parses for each sentence. This ...
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Improving Text Normalization via Unsupervised Model and Discriminative Reranking
... Maxent reranking above), we can also use contex- tual information for training the ...Maxent reranking method as above is used, which optimizes the word level ...
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Concept to text Generation via Discriminative Reranking
... During training, our algorithm is given a corpus consisting of several scenarios, i.e., database records paired with texts like those shown in Figure 1. The database (and accompanying texts) are next con- verted into a ...
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Discriminative Reranking of Discourse Parses Using Tree Kernels
... We also investigate the impact of traditional (i.e., not subtree) features for reranking discourse parses. Our feature vector comprises two types of features that capture global properties of the DTs. Basic ...
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Discriminative Reranking for Spelling Correction
... the discriminative models, Winnow [8], neural net [10] and maximum entropy [16] are ...linearly discriminative, which can integrate some cutting-edge techniques into this ...
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Discriminative Reranking for Natural Language Parsing
... The remainder of this article is structured as follows. Section 2 reviews history- based models for NLP and highlights the perceived shortcomings of history-based models which motivate the reranking approaches ...
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Efficient Stacked Dependency Parsing by Forest Reranking
... through discriminative reranking with higher-order graph-based features, which works on the forests output by the first-stage dynamic pro- gramming shift-reduce parser and integrates non- local features ...
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Adaptation of Statistical Machine Translation Model for Cross Lingual Information Retrieval in a Service Context
... the reranking framework to different NLP tasks such as Named Entities Extraction (Collins, 2001), parsing (Collins and Roark, 2004), and language modelling (Roark et ...the reranking framework to combine ...
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Large scale discriminative language model reranking for voice search
... scale discriminative language models that can be integrated within a large vocabulary con- tinuous speech recognition (LVCSR) system using lattice ...our discriminative reranking ...
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Forest Reranking: Discriminative Parsing with Non Local Features
... Discriminative reranking has become a popular technique for many NLP problems, in particular, parsing (Collins, 2000) and machine translation (Shen et ...
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Perceptron Reranking for CCG Realization
... how discriminative reranking with an averaged perceptron model can be used to achieve substantial improvements in re- alization quality with ...on discriminative training with log linear models for ...
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Analysis of Patterns in Data Mining
... of discriminative patterns a set of training instances and features are taken as input and feature selection is iteratively performed on them and the feature with the highest discriminative power is ...
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Reranking for Neural Semantic Parsing
... of reranking the beam of can- didate parses has been attempted for various NLP tasks (Collins and Koo, 2000), and was also previously applied for classical grammar- driven semantic ...Such reranking mod- ...
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