Get To The Point: Summarization with Pointer-Generator ...

Germany beat Argentina 2-0 the model may attend to the words victorious and win in the source text. et al.,2014), in which recurrent neural networks (RNNs) both read and freely generate text, has made abstractive summarization viable (Chopra et al.,2016;Nallapati et al.,2016;Rush et al., 2015;Zeng et al.,2016). Though these systems

  Generators, Protein, Victorious, Pointer generator

Statistical Machine Translation of French and German into ...

French sentence pairs based on the likelihood that one is a trans- lation of the other, and a decoder attempts to find the English sentence for which the product of the language and translation

  Machine, Statistical, French, Translation, Statistical machine translation of french

A Fast and Accurate Dependency Parser using Neural Networks

ing algorithm but in the feature extraction step (He et al., 2013). For instance, Bohnet (2010) reports that his baseline parser spends 99% of its time do-ing feature extraction, despite that being done in standard efficient ways. In this work, we address all of these problems by using dense features in place of the sparse indi-cator features.

  Feature, Using, Dependency

Introduction to Information Retrieval

Apr 01, 2009 · CLASSIFICATION ing queries belong, we now introduce the general notion of a classification problem. Given a set of classes, we seek to determine which class(es) a given ... Books in a library are assigned Library of Congress categories by a librarian. But manual classification is

  General, Library, Classification, Congress, Library of congress

Generalized Linear Mixed Models (illustrated with R on ...

Generalized Linear Mixed Models (illustrated with R on Bresnan et al.’s datives data) Christopher Manning 23 November 2007 In this handout, I present the logistic model with fixed and random effects, a form of Generalized Linear Mixed Model (GLMM). I illustrate this with an analysis of Bresnan et al. (2005)’s dative data (the version

  Linear, Mixed, Generalized, Generalized linear mixed

BERT: Pre-training of Deep Bidirectional Transformers for ...

Imagine it’s 2013: Well-tuned 2-layer, 512-dim LSTM sentiment analysis gets 80% accuracy, training for 8 hours. Pre-train LM on same architecture for a week, get 80.5%.

  Analysis, Rebt, Sentiment, Sentiment analysis

Recursive Deep Models for Semantic Compositionality Over a ...

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank Richard Socher, Alex Perelygin, Jean Y. Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng and Christopher Potts

Collocations - Stanford University

The twenty highest ranking phrases containing strong and powerful all have the form A N (where A is either strong or powerful). We have listed them in Table 5.4. Again, given the simplicity of the method, these results are surprisingly accurate. For example, they give evidence that strong challenge and powerful

  Powerful, Phrases, Collocations

GloVe: Global Vectors for Word Representation

Collobert, 2014) has been suggested as an effec-tive way of learning word representations. Shallow Window-Based Methods. Another approach is to learn word representations that aid in making predictions within local context win-dows. For example, Bengio et al. (2003) intro-duced a model that learns word vector representa-

  Gloves, Viet, Eff ective, Effec

LDAvis: A method for visualizing and interpreting topics

ics. This two-stage process yields good results on experimental data, although the resulting output is still simply a ranked list containing a mixture of terms and n-grams, and the usefulness of the method for topic interpretation was not tested in a user study. Newman et al. (2010) describe a method for ranking terms within topics to aid ...

  Process, Topics

Eklablog

Created Date: 8/3/2012 4:11:55 PM

arxiv.org

Created Date: 20170421000942Z

GloVe: Global Vectors for Word Representation

et al., 2008), document classification (Sebastiani, 2002), question answering (Tellex et al., 2003), named entity recognition (Turian et al., 2010), and parsing (Socher et al., 2013). Most word vector methods rely on the distance or angle between pairs of word vectors as the pri-mary method for evaluating the intrinsic quality

  Gloves

The Relationship Between Precision-Recall and ROC Curves

these spaces (Davis et al., 2005). The goal in ROC space is to be in the upper-left-hand corner, and when one looks at the ROC curves in Figure 1(a) they ap-pear to be fairly close to optimal. In PR space the goal is to be in the upper-right-hand corner, and the PR curves in Figure 1(b) show that there is still vast room for improvement.

DEMANDE DE PARRAINAGE, ENTENTE DE PARRAINAGE ET …

Immigration, Refugiés et Citoyenneté Canada \(IRCC\) Subject \r\n Created Date: 10/31/2018 2:05:28 PM ...

ET-300 302 Owner's Manual - E-Collar

-coGr . Title: ET-300 302 Owner's Manual Created Date: 4/18/2019 3:54:07 PM

Form ET-141:1/15:New York Estate Tax Domicile Affidavit:et141

ET-141 (1/15) Period of time from - to Address Residence owned - rented other - explain Period of time from - to Address Residence owned - rented other - explain 6 For the five years prior to death, list (1) the Internal Revenue Service Centers and (2) …