Paper Group NANR 179
Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua. Initiations and Interruptions in a Spoken Dialog System. Showing versus doing: Teaching by demonstration. TransRead: Designing a Bilingual Reading Experience with Machine Translation Technologies. Domain Specific Named Entity Recognition Referring to the …
Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua
| Title | Mapping Verbs in Different Languages to Knowledge Base Relations using Web Text as Interlingua |
| Authors | Derry Tanti Wijaya, Tom M. Mitchell |
| Abstract | |
| Tasks | Machine Translation, Reading Comprehension, Relation Extraction |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1096/ |
| https://www.aclweb.org/anthology/N16-1096 | |
| PWC | https://paperswithcode.com/paper/mapping-verbs-in-different-languages-to |
| Repo | |
| Framework | |
Initiations and Interruptions in a Spoken Dialog System
| Title | Initiations and Interruptions in a Spoken Dialog System |
| Authors | Leah Nicolich-Henkin, Carolyn Ros{'e}, Alan W Black |
| Abstract | |
| Tasks | |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3618/ |
| https://www.aclweb.org/anthology/W16-3618 | |
| PWC | https://paperswithcode.com/paper/initiations-and-interruptions-in-a-spoken |
| Repo | |
| Framework | |
Showing versus doing: Teaching by demonstration
| Title | Showing versus doing: Teaching by demonstration |
| Authors | Mark K. Ho, Michael Littman, James Macglashan, Fiery Cushman, Joseph L. Austerweil |
| Abstract | People often learn from others’ demonstrations, and classic inverse reinforcement learning (IRL) algorithms have brought us closer to realizing this capacity in machines. In contrast, teaching by demonstration has been less well studied computationally. Here, we develop a novel Bayesian model for teaching by demonstration. Stark differences arise when demonstrators are intentionally teaching a task versus simply performing a task. In two experiments, we show that human participants systematically modify their teaching behavior consistent with the predictions of our model. Further, we show that even standard IRL algorithms benefit when learning from behaviors that are intentionally pedagogical. We conclude by discussing IRL algorithms that can take advantage of intentional pedagogy. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6413-showing-versus-doing-teaching-by-demonstration |
| http://papers.nips.cc/paper/6413-showing-versus-doing-teaching-by-demonstration.pdf | |
| PWC | https://paperswithcode.com/paper/showing-versus-doing-teaching-by |
| Repo | |
| Framework | |
TransRead: Designing a Bilingual Reading Experience with Machine Translation Technologies
| Title | TransRead: Designing a Bilingual Reading Experience with Machine Translation Technologies |
| Authors | Fran{\c{c}}ois Yvon, Yong Xu, Marianna Apidianaki, Cl{'e}ment Pillias, Pierre Cubaud |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-3006/ |
| https://www.aclweb.org/anthology/N16-3006 | |
| PWC | https://paperswithcode.com/paper/transread-designing-a-bilingual-reading |
| Repo | |
| Framework | |
Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks
| Title | Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks |
| Authors | Suzushi Tomori, Takashi Ninomiya, Shinsuke Mori |
| Abstract | |
| Tasks | Machine Translation, Named Entity Recognition, Part-Of-Speech Tagging, Sentiment Analysis |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2039/ |
| https://www.aclweb.org/anthology/P16-2039 | |
| PWC | https://paperswithcode.com/paper/domain-specific-named-entity-recognition |
| Repo | |
| Framework | |
Extraction of Bilingual Technical Terms for Chinese-Japanese Patent Translation
| Title | Extraction of Bilingual Technical Terms for Chinese-Japanese Patent Translation |
| Authors | Wei Yang, Jinghui Yan, Yves Lepage |
| Abstract | |
| Tasks | Language Modelling, Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-2012/ |
| https://www.aclweb.org/anthology/N16-2012 | |
| PWC | https://paperswithcode.com/paper/extraction-of-bilingual-technical-terms-for |
| Repo | |
| Framework | |
SweLLex: Second language learners’ productive vocabulary
| Title | SweLLex: Second language learners’ productive vocabulary |
| Authors | Elena Volodina, Ildik{'o} Pil{'a}n, Lorena Llozhi, Baptiste Degryse, Thomas Fran{\c{c}}ois |
| Abstract | |
| Tasks | |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/W16-6510/ |
| https://www.aclweb.org/anthology/W16-6510 | |
| PWC | https://paperswithcode.com/paper/swellex-second-language-learnersa-productive |
| Repo | |
| Framework | |
Verification Based Solution for Structured MAB Problems
| Title | Verification Based Solution for Structured MAB Problems |
| Authors | Zohar S. Karnin |
| Abstract | We consider the problem of finding the best arm in a stochastic Mutli-armed Bandit (MAB) game and propose a general framework based on verification that applies to multiple well-motivated generalizations of the classic MAB problem. In these generalizations, additional structure is known in advance, causing the task of verifying the optimality of a candidate to be easier than discovering the best arm. Our results are focused on the scenario where the failure probability $\delta$ must be very low; we essentially show that in this high confidence regime, identifying the best arm is as easy as the task of verification. We demonstrate the effectiveness of our framework by applying it, and improving the state-of-the art results in the problems of: Linear bandits, Dueling bandits with the Condorcet assumption, Copeland dueling bandits, Unimodal bandits and Graphical bandits. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6525-verification-based-solution-for-structured-mab-problems |
| http://papers.nips.cc/paper/6525-verification-based-solution-for-structured-mab-problems.pdf | |
| PWC | https://paperswithcode.com/paper/verification-based-solution-for-structured |
| Repo | |
| Framework | |
Large-Scale Price Optimization via Network Flow
| Title | Large-Scale Price Optimization via Network Flow |
| Authors | Shinji Ito, Ryohei Fujimaki |
| Abstract | This paper deals with price optimization, which is to find the best pricing strategy that maximizes revenue or profit, on the basis of demand forecasting models. Though recent advances in regression technologies have made it possible to reveal price-demand relationship of a number of multiple products, most existing price optimization methods, such as mixed integer programming formulation, cannot handle tens or hundreds of products because of their high computational costs. To cope with this problem, this paper proposes a novel approach based on network flow algorithms. We reveal a connection between supermodularity of the revenue and cross elasticity of demand. On the basis of this connection, we propose an efficient algorithm that employs network flow algorithms. The proposed algorithm can handle hundreds or thousands of products, and returns an exact optimal solution under an assumption regarding cross elasticity of demand. Even in case in which the assumption does not hold, the proposed algorithm can efficiently find approximate solutions as good as can other state-of-the-art methods, as empirical results show. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6301-large-scale-price-optimization-via-network-flow |
| http://papers.nips.cc/paper/6301-large-scale-price-optimization-via-network-flow.pdf | |
| PWC | https://paperswithcode.com/paper/large-scale-price-optimization-via-network |
| Repo | |
| Framework | |
Text Retrieval by Term Co-occurrences in a Query-based Vector Space
| Title | Text Retrieval by Term Co-occurrences in a Query-based Vector Space |
| Authors | Eriks Sneiders |
| Abstract | Term co-occurrence in a sentence or paragraph is a powerful and often overlooked feature for text matching in document retrieval. In our experiments with matching email-style query messages to webpages, such term co-occurrence helped greatly to filter and rank documents, compared to matching document-size bags-of-words. The paper presents the results of the experiments as well as a text-matching model where the query shapes the vector space, a document is modelled by two or three vectors in this vector space, and the query-document similarity score depends on the length of the vectors and the relationships between them. |
| Tasks | Text Categorization, Text Matching |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1222/ |
| https://www.aclweb.org/anthology/C16-1222 | |
| PWC | https://paperswithcode.com/paper/text-retrieval-by-term-co-occurrences-in-a |
| Repo | |
| Framework | |
I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter
| Title | I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter |
| Authors | Zhengchen Zhang, Chen Zhang, Fuxiang Wu, Dong-Yan Huang, Weisi Lin, Minghui Dong |
| Abstract | |
| Tasks | Emotion Recognition, Information Retrieval, Music Information Retrieval, Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1008/ |
| https://www.aclweb.org/anthology/S16-1008 | |
| PWC | https://paperswithcode.com/paper/i2rntu-at-semeval-2016-task-4-classifier |
| Repo | |
| Framework | |
SteM at SemEval-2016 Task 4: Applying Active Learning to Improve Sentiment Classification
| Title | SteM at SemEval-2016 Task 4: Applying Active Learning to Improve Sentiment Classification |
| Authors | Stefan R{"a}biger, Mishal Kazmi, Y{"u}cel Sayg{\i}n, Peter Sch{"u}ller, Myra Spiliopoulou |
| Abstract | |
| Tasks | Active Learning, Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1007/ |
| https://www.aclweb.org/anthology/S16-1007 | |
| PWC | https://paperswithcode.com/paper/stem-at-semeval-2016-task-4-applying-active |
| Repo | |
| Framework | |
Modelling the Interpretation of Discourse Connectives by Bayesian Pragmatics
| Title | Modelling the Interpretation of Discourse Connectives by Bayesian Pragmatics |
| Authors | Frances Yung, Kevin Duh, Taku Komura, Yuji Matsumoto |
| Abstract | |
| Tasks | Bayesian Inference |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2086/ |
| https://www.aclweb.org/anthology/P16-2086 | |
| PWC | https://paperswithcode.com/paper/modelling-the-interpretation-of-discourse |
| Repo | |
| Framework | |
The Social Impact of Natural Language Processing
| Title | The Social Impact of Natural Language Processing |
| Authors | Dirk Hovy, Shannon L. Spruit |
| Abstract | |
| Tasks | |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2096/ |
| https://www.aclweb.org/anthology/P16-2096 | |
| PWC | https://paperswithcode.com/paper/the-social-impact-of-natural-language |
| Repo | |
| Framework | |
Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System
| Title | Automatic Recognition of Conversational Strategies in the Service of a Socially-Aware Dialog System |
| Authors | Ran Zhao, Tanmay Sinha, Alan Black, Justine Cassell |
| Abstract | |
| Tasks | |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3647/ |
| https://www.aclweb.org/anthology/W16-3647 | |
| PWC | https://paperswithcode.com/paper/automatic-recognition-of-conversational |
| Repo | |
| Framework | |
