May 5, 2019

1608 words 8 mins read

Paper Group NANR 82

Paper Group NANR 82

Semiparametric Differential Graph Models. Learning Bayesian networks with ancestral constraints. Automated scoring across different modalities. Constraint-Based Bilingual Lexicon Induction for Closely Related Languages. A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant. Generalized Transition-based Dependency …

Semiparametric Differential Graph Models

Title Semiparametric Differential Graph Models
Authors Pan Xu, Quanquan Gu
Abstract In many cases of network analysis, it is more attractive to study how a network varies under different conditions than an individual static network. We propose a novel graphical model, namely Latent Differential Graph Model, where the networks under two different conditions are represented by two semiparametric elliptical distributions respectively, and the variation of these two networks (i.e., differential graph) is characterized by the difference between their latent precision matrices. We propose an estimator for the differential graph based on quasi likelihood maximization with nonconvex regularization. We show that our estimator attains a faster statistical rate in parameter estimation than the state-of-the-art methods, and enjoys oracle property under mild conditions. Thorough experiments on both synthetic and real world data support our theory.
Tasks
Published 2016-12-01
URL http://papers.nips.cc/paper/6529-semiparametric-differential-graph-models
PDF http://papers.nips.cc/paper/6529-semiparametric-differential-graph-models.pdf
PWC https://paperswithcode.com/paper/semiparametric-differential-graph-models
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Learning Bayesian networks with ancestral constraints

Title Learning Bayesian networks with ancestral constraints
Authors Eunice Yuh-Jie Chen, Yujia Shen, Arthur Choi, Adnan Darwiche
Abstract We consider the problem of learning Bayesian networks optimally, when subject to background knowledge in the form of ancestral constraints. Our approach is based on a recently proposed framework for optimal structure learning based on non-decomposable scores, which is general enough to accommodate ancestral constraints. The proposed framework exploits oracles for learning structures using decomposable scores, which cannot accommodate ancestral constraints since they are non-decomposable. We show how to empower these oracles by passing them decomposable constraints that they can handle, which are inferred from ancestral constraints that they cannot handle. Empirically, we demonstrate that our approach can be orders-of-magnitude more efficient than alternative frameworks, such as those based on integer linear programming.
Tasks
Published 2016-12-01
URL http://papers.nips.cc/paper/6386-learning-bayesian-networks-with-ancestral-constraints
PDF http://papers.nips.cc/paper/6386-learning-bayesian-networks-with-ancestral-constraints.pdf
PWC https://paperswithcode.com/paper/learning-bayesian-networks-with-ancestral
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Automated scoring across different modalities

Title Automated scoring across different modalities
Authors Anastassia Loukina, Aoife Cahill
Abstract
Tasks Speech Recognition
Published 2016-06-01
URL https://www.aclweb.org/anthology/W16-0514/
PDF https://www.aclweb.org/anthology/W16-0514
PWC https://paperswithcode.com/paper/automated-scoring-across-different-modalities
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Title Constraint-Based Bilingual Lexicon Induction for Closely Related Languages
Authors Arbi Haza Nasution, Yohei Murakami, Toru Ishida
Abstract The lack or absence of parallel and comparable corpora makes bilingual lexicon extraction becomes a difficult task for low-resource languages. Pivot language and cognate recognition approach have been proven useful to induce bilingual lexicons for such languages. We analyze the features of closely related languages and define a semantic constraint assumption. Based on the assumption, we propose a constraint-based bilingual lexicon induction for closely related languages by extending constraints and translation pair candidates from recent pivot language approach. We further define three constraint sets based on language characteristics. In this paper, two controlled experiments are conducted. The former involves four closely related language pairs with different language pair similarities, and the latter focuses on sense connectivity between non-pivot words and pivot words. We evaluate our result with F-measure. The result indicates that our method works better on voluminous input dictionaries and high similarity languages. Finally, we introduce a strategy to use proper constraint sets for different goals and language characteristics.
Tasks
Published 2016-05-01
URL https://www.aclweb.org/anthology/L16-1524/
PDF https://www.aclweb.org/anthology/L16-1524
PWC https://paperswithcode.com/paper/constraint-based-bilingual-lexicon-induction
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A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant

Title A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant
Authors SangJe Cho, Jong-Ho Shin, Hong-Bae Jun, Ho-Jin Hwang, Chunghun Ha, Jinsang Hwang
Abstract The offshore plant equipment usually has a long life cycle. During its O&M (Operation and Maintenance) phase, since the accidental occurrence of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical offshore equipment. Nowadays, due to the emerging ICTs (Information Communication Technologies), it is possible to send health monitoring information to administrator of an offshore plant, which leads to much concern on CBM (ConditionBased Maintenance). This study introduces three approaches for predicting the next failure time of offshore plant equipment (gas compressor) with case studies, which are based on finite state continuous time Markov model, linear regression method, and their hybrid model
Tasks
Published 2016-10-03
URL http://dx.doi.org/10.1155/2016/8705796
PDF http://dx.doi.org/10.1155/2016/8705796
PWC https://paperswithcode.com/paper/a-study-on-estimating-the-next-failure-time
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Generalized Transition-based Dependency Parsing via Control Parameters

Title Generalized Transition-based Dependency Parsing via Control Parameters
Authors Bernd Bohnet, Ryan McDonald, Emily Pitler, Ji Ma
Abstract
Tasks Dependency Parsing, Transition-Based Dependency Parsing
Published 2016-08-01
URL https://www.aclweb.org/anthology/P16-1015/
PDF https://www.aclweb.org/anthology/P16-1015
PWC https://paperswithcode.com/paper/generalized-transition-based-dependency
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The Language Application Grid and Galaxy

Title The Language Application Grid and Galaxy
Authors Nancy Ide, Keith Suderman, James Pustejovsky, Marc Verhagen, Christopher Cieri
Abstract The NSF-SI2-funded LAPPS Grid project is a collaborative effort among Brandeis University, Vassar College, Carnegie-Mellon University (CMU), and the Linguistic Data Consortium (LDC), which has developed an open, web-based infrastructure through which resources can be easily accessed and within which tailored language services can be efficiently composed, evaluated, disseminated and consumed by researchers, developers, and students across a wide variety of disciplines. The LAPPS Grid project recently adopted Galaxy (Giardine et al., 2005), a robust, well-developed, and well-supported front end for workflow configuration, management, and persistence. Galaxy allows data inputs and processing steps to be selected from graphical menus, and results are displayed in intuitive plots and summaries that encourage interactive workflows and the exploration of hypotheses. The Galaxy workflow engine provides significant advantages for deploying pipelines of LAPPS Grid web services, including not only means to create and deploy locally-run and even customized versions of the LAPPS Grid as well as running the LAPPS Grid in the cloud, but also access to a huge array of statistical and visualization tools that have been developed for use in genomics research.
Tasks
Published 2016-05-01
URL https://www.aclweb.org/anthology/L16-1073/
PDF https://www.aclweb.org/anthology/L16-1073
PWC https://paperswithcode.com/paper/the-language-application-grid-and-galaxy
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B2SG: a TOEFL-like Task for Portuguese

Title B2SG: a TOEFL-like Task for Portuguese
Authors Rodrigo Wilkens, Leonardo Zilio, Eduardo Ferreira, Aline Villavicencio
Abstract Resources such as WordNet are useful for NLP applications, but their manual construction consumes time and personnel, and frequently results in low coverage. One alternative is the automatic construction of large resources from corpora like distributional thesauri, containing semantically associated words. However, as they may contain noise, there is a strong need for automatic ways of evaluating the quality of the resulting resource. This paper introduces a gold standard that can aid in this task. The BabelNet-Based Semantic Gold Standard (B2SG) was automatically constructed based on BabelNet and partly evaluated by human judges. It consists of sets of tests that present one target word, one related word and three unrelated words. B2SG contains 2,875 validated relations: 800 for verbs and 2,075 for nouns; these relations are divided among synonymy, antonymy and hypernymy. They can be used as the basis for evaluating the accuracy of the similarity relations on distributional thesauri by comparing the proximity of the target word with the related and unrelated options and observing if the related word has the highest similarity value among them. As a case study two distributional thesauri were also developed: one using surface forms from a large (1.5 billion word) corpus and the other using lemmatized forms from a smaller (409 million word) corpus. Both distributional thesauri were then evaluated against B2SG, and the one using lemmatized forms performed slightly better.
Tasks
Published 2016-05-01
URL https://www.aclweb.org/anthology/L16-1580/
PDF https://www.aclweb.org/anthology/L16-1580
PWC https://paperswithcode.com/paper/b2sg-a-toefl-like-task-for-portuguese
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An Annotated Corpus of Direct Speech

Title An Annotated Corpus of Direct Speech
Authors John Lee, Chak Yan Yeung
Abstract We propose a scheme for annotating direct speech in literary texts, based on the Text Encoding Initiative (TEI) and the coreference annotation guidelines from the Message Understanding Conference (MUC). The scheme encodes the speakers and listeners of utterances in a text, as well as the quotative verbs that reports the utterances. We measure inter-annotator agreement on this annotation task. We then present statistics on a manually annotated corpus that consists of books from the New Testament. Finally, we visualize the corpus as a conversational network.
Tasks
Published 2016-05-01
URL https://www.aclweb.org/anthology/L16-1168/
PDF https://www.aclweb.org/anthology/L16-1168
PWC https://paperswithcode.com/paper/an-annotated-corpus-of-direct-speech
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Bi-Transferring Deep Neural Networks for Domain Adaptation

Title Bi-Transferring Deep Neural Networks for Domain Adaptation
Authors Guangyou Zhou, Zhiwen Xie, Jimmy Xiangji Huang, Tingting He
Abstract
Tasks Domain Adaptation, Sentiment Analysis
Published 2016-08-01
URL https://www.aclweb.org/anthology/P16-1031/
PDF https://www.aclweb.org/anthology/P16-1031
PWC https://paperswithcode.com/paper/bi-transferring-deep-neural-networks-for
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Temporal Anchoring of Events for the TimeBank Corpus

Title Temporal Anchoring of Events for the TimeBank Corpus
Authors Nils Reimers, Nazanin Dehghani, Iryna Gurevych
Abstract
Tasks
Published 2016-08-01
URL https://www.aclweb.org/anthology/P16-1207/
PDF https://www.aclweb.org/anthology/P16-1207
PWC https://paperswithcode.com/paper/temporal-anchoring-of-events-for-the-timebank
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Set-Theoretic Alignment for Comparable Corpora

Title Set-Theoretic Alignment for Comparable Corpora
Authors Thierry Etchegoyhen, Andoni Azpeitia
Abstract
Tasks Machine Translation
Published 2016-08-01
URL https://www.aclweb.org/anthology/P16-1189/
PDF https://www.aclweb.org/anthology/P16-1189
PWC https://paperswithcode.com/paper/set-theoretic-alignment-for-comparable
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A Compositional-Distributional Semantic Model for Searching Complex Entity Categories

Title A Compositional-Distributional Semantic Model for Searching Complex Entity Categories
Authors Juliano Efson Sales, Andr{'e} Freitas, Brian Davis, H, Siegfried schuh
Abstract
Tasks Information Retrieval, Named Entity Recognition
Published 2016-08-01
URL https://www.aclweb.org/anthology/S16-2025/
PDF https://www.aclweb.org/anthology/S16-2025
PWC https://paperswithcode.com/paper/a-compositional-distributional-semantic-model
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Crowd-sourcing NLG Data: Pictures Elicit Better Data.

Title Crowd-sourcing NLG Data: Pictures Elicit Better Data.
Authors Jekaterina Novikova, Oliver Lemon, Verena Rieser
Abstract
Tasks Semantic Parsing, Spoken Dialogue Systems, Text Generation
Published 2016-09-01
URL https://www.aclweb.org/anthology/W16-6644/
PDF https://www.aclweb.org/anthology/W16-6644
PWC https://paperswithcode.com/paper/crowd-sourcing-nlg-data-pictures-elicit
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Towards Generating Colour Terms for Referents in Photographs: Prefer the Expected or the Unexpected?

Title Towards Generating Colour Terms for Referents in Photographs: Prefer the Expected or the Unexpected?
Authors Sina Zarrie{\ss}, David Schlangen
Abstract
Tasks Text Generation
Published 2016-09-01
URL https://www.aclweb.org/anthology/W16-6642/
PDF https://www.aclweb.org/anthology/W16-6642
PWC https://paperswithcode.com/paper/towards-generating-colour-terms-for-referents
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