Paper Group NANR 216
How Do Cultural Differences Impact the Quality of Sarcasm Annotation?: A Case Study of Indian Annotators and American Text. Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships. LexFr: Adapting the LexIt Framework to Build a Corpus-based French Subcategorization Lexicon. Simple and Efficient Weighted Minwis …
How Do Cultural Differences Impact the Quality of Sarcasm Annotation?: A Case Study of Indian Annotators and American Text
| Title | How Do Cultural Differences Impact the Quality of Sarcasm Annotation?: A Case Study of Indian Annotators and American Text |
| Authors | Aditya Joshi, Pushpak Bhattacharyya, Mark Carman, Jaya Saraswati, Rajita Shukla |
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| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2111/ |
| https://www.aclweb.org/anthology/W16-2111 | |
| PWC | https://paperswithcode.com/paper/how-do-cultural-differences-impact-the |
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Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships
| Title | Feuding Families and Former Friends: Unsupervised Learning for Dynamic Fictional Relationships |
| Authors | Mohit Iyyer, Anupam Guha, Snigdha Chaturvedi, Jordan Boyd-Graber, Hal Daum{'e} III |
| Abstract | |
| Tasks | Dictionary Learning |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1180/ |
| https://www.aclweb.org/anthology/N16-1180 | |
| PWC | https://paperswithcode.com/paper/feuding-families-and-former-friends |
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LexFr: Adapting the LexIt Framework to Build a Corpus-based French Subcategorization Lexicon
| Title | LexFr: Adapting the LexIt Framework to Build a Corpus-based French Subcategorization Lexicon |
| Authors | Giulia Rambelli, Gianluca Lebani, Laurent Pr{'e}vot, Aless Lenci, ro |
| Abstract | This paper introduces LexFr, a corpus-based French lexical resource built by adapting the framework LexIt, originally developed to describe the combinatorial potential of Italian predicates. As in the original framework, the behavior of a group of target predicates is characterized by a series of syntactic (i.e., subcategorization frames) and semantic (i.e., selectional preferences) statistical information (a.k.a. distributional profiles) whose extraction process is mostly unsupervised. The first release of LexFr includes information for 2,493 verbs, 7,939 nouns and 2,628 adjectives. In these pages we describe the adaptation process and evaluated the final resource by comparing the information collected for 20 test verbs against the information available in a gold standard dictionary. In the best performing setting, we obtained 0.74 precision, 0.66 recall and 0.70 F-measure. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1148/ |
| https://www.aclweb.org/anthology/L16-1148 | |
| PWC | https://paperswithcode.com/paper/lexfr-adapting-the-lexit-framework-to-build-a |
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Simple and Efficient Weighted Minwise Hashing
| Title | Simple and Efficient Weighted Minwise Hashing |
| Authors | Anshumali Shrivastava |
| Abstract | Weighted minwise hashing (WMH) is one of the fundamental subroutine, required by many celebrated approximation algorithms, commonly adopted in industrial practice for large -scale search and learning. The resource bottleneck with WMH is the computation of multiple (typically a few hundreds to thousands) independent hashes of the data. We propose a simple rejection type sampling scheme based on a carefully designed red-green map, where we show that the number of rejected sample has exactly the same distribution as weighted minwise sampling. The running time of our method, for many practical datasets, is an order of magnitude smaller than existing methods. Experimental evaluations, on real datasets, show that for computing 500 WMH, our proposal can be 60000x faster than the Ioffe’s method without losing any accuracy. Our method is also around 100x faster than approximate heuristics capitalizing on the efficient ``densified” one permutation hashing schemes~\cite{Proc:OneHashLSH_ICML14,Proc:Shrivastava_UAI14}. Given the simplicity of our approach and its significant advantages, we hope that it will replace existing implementations in practice. | |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6472-simple-and-efficient-weighted-minwise-hashing |
| http://papers.nips.cc/paper/6472-simple-and-efficient-weighted-minwise-hashing.pdf | |
| PWC | https://paperswithcode.com/paper/simple-and-efficient-weighted-minwise-hashing |
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非負矩陣分解法於語音調變頻譜強化之研究(A study of enhancing the modulation spectrum of speech signals via nonnegative matrix factorization)[In Chinese]
| Title | 非負矩陣分解法於語音調變頻譜強化之研究(A study of enhancing the modulation spectrum of speech signals via nonnegative matrix factorization)[In Chinese] |
| Authors | Xu-Xiang Wang, Zhi-Hao Zheng, Yu Tsao, Jhih-Wei Hong |
| Abstract | |
| Tasks | Speech Enhancement |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/O16-1018/ |
| https://www.aclweb.org/anthology/O16-1018 | |
| PWC | https://paperswithcode.com/paper/ee2-ceae314eae3eaee-ea14aa1c-ca-study-of |
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Generalization in Artificial Language Learning: Modelling the Propensity to Generalize
| Title | Generalization in Artificial Language Learning: Modelling the Propensity to Generalize |
| Authors | Raquel G. Alhama, Willem Zuidema |
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| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-1909/ |
| https://www.aclweb.org/anthology/W16-1909 | |
| PWC | https://paperswithcode.com/paper/generalization-in-artificial-language |
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Semi-automated annotation of page-based documents within the Genre and Multimodality framework
| Title | Semi-automated annotation of page-based documents within the Genre and Multimodality framework |
| Authors | Tuomo Hiippala |
| Abstract | |
| Tasks | Optical Character Recognition |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2109/ |
| https://www.aclweb.org/anthology/W16-2109 | |
| PWC | https://paperswithcode.com/paper/semi-automated-annotation-of-page-based |
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Differential Privacy without Sensitivity
| Title | Differential Privacy without Sensitivity |
| Authors | Kentaro Minami, Hitomi Arai, Issei Sato, Hiroshi Nakagawa |
| Abstract | The exponential mechanism is a general method to construct a randomized estimator that satisfies $(\varepsilon, 0)$-differential privacy. Recently, Wang et al. showed that the Gibbs posterior, which is a data-dependent probability distribution that contains the Bayesian posterior, is essentially equivalent to the exponential mechanism under certain boundedness conditions on the loss function. While the exponential mechanism provides a way to build an $(\varepsilon, 0)$-differential private algorithm, it requires boundedness of the loss function, which is quite stringent for some learning problems. In this paper, we focus on $(\varepsilon, \delta)$-differential privacy of Gibbs posteriors with convex and Lipschitz loss functions. Our result extends the classical exponential mechanism, allowing the loss functions to have an unbounded sensitivity. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6050-differential-privacy-without-sensitivity |
| http://papers.nips.cc/paper/6050-differential-privacy-without-sensitivity.pdf | |
| PWC | https://paperswithcode.com/paper/differential-privacy-without-sensitivity |
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Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News
| Title | Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News |
| Authors | Victoria Rubin, Niall Conroy, Yimin Chen, Sarah Cornwell |
| Abstract | |
| Tasks | Deception Detection |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0802/ |
| https://www.aclweb.org/anthology/W16-0802 | |
| PWC | https://paperswithcode.com/paper/fake-news-or-truth-using-satirical-cues-to |
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Can We Make Computers Laugh at Talks?
| Title | Can We Make Computers Laugh at Talks? |
| Authors | Chong Min Lee, Su-Youn Yoon, Lei Chen |
| Abstract | Considering the importance of public speech skills, a system which makes a prediction on where audiences laugh in a talk can be helpful to a person who prepares for a talk. We investigated a possibility that a state-of-the-art humor recognition system can be used in detecting sentences inducing laughters in talks. In this study, we used TED talks and laughters in the talks as data. Our results showed that the state-of-the-art system needs to be improved in order to be used in a practical application. In addition, our analysis showed that classifying humorous sentences in talks is very challenging due to close distance between humorous and non-humorous sentences. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4319/ |
| https://www.aclweb.org/anthology/W16-4319 | |
| PWC | https://paperswithcode.com/paper/can-we-make-computers-laugh-at-talks |
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The SIGMORPHON 2016 Shared Task—Morphological Reinflection
| Title | The SIGMORPHON 2016 Shared Task—Morphological Reinflection |
| Authors | Ryan Cotterell, Christo Kirov, John Sylak-Glassman, David Yarowsky, Jason Eisner, Mans Hulden |
| Abstract | |
| Tasks | Morphological Analysis |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2002/ |
| https://www.aclweb.org/anthology/W16-2002 | |
| PWC | https://paperswithcode.com/paper/the-sigmorphon-2016-shared-taskamorphological |
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Evaluating and Combining Name Entity Recognition Systems
| Title | Evaluating and Combining Name Entity Recognition Systems |
| Authors | Ridong Jiang, Rafael E. Banchs, Haizhou Li |
| Abstract | |
| Tasks | Information Retrieval, Machine Translation, Named Entity Recognition, Question Answering |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2703/ |
| https://www.aclweb.org/anthology/W16-2703 | |
| PWC | https://paperswithcode.com/paper/evaluating-and-combining-name-entity |
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An algorithm for L1 nearest neighbor search via monotonic embedding
| Title | An algorithm for L1 nearest neighbor search via monotonic embedding |
| Authors | Xinan Wang, Sanjoy Dasgupta |
| Abstract | Fast algorithms for nearest neighbor (NN) search have in large part focused on L2 distance. Here we develop an approach for L1 distance that begins with an explicit and exact embedding of the points into L2. We show how this embedding can efficiently be combined with random projection methods for L2 NN search, such as locality-sensitive hashing or random projection trees. We rigorously establish the correctness of the methodology and show by experimentation that it is competitive in practice with available alternatives. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6227-an-algorithm-for-l1-nearest-neighbor-search-via-monotonic-embedding |
| http://papers.nips.cc/paper/6227-an-algorithm-for-l1-nearest-neighbor-search-via-monotonic-embedding.pdf | |
| PWC | https://paperswithcode.com/paper/an-algorithm-for-l1-nearest-neighbor-search |
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Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions
| Title | Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions |
| Authors | Yichen Wang, Nan Du, Rakshit Trivedi, Le Song |
| Abstract | Matching users to the right items at the right time is a fundamental task in recommendation systems. As users interact with different items over time, users’ and items’ feature may evolve and co-evolve over time. Traditional models based on static latent features or discretizing time into epochs can become ineffective for capturing the fine-grained temporal dynamics in the user-item interactions. We propose a coevolutionary latent feature process model that accurately captures the coevolving nature of users’ and items’ feature. To learn parameters, we design an efficient convex optimization algorithm with a novel low rank space sharing constraints. Extensive experiments on diverse real-world datasets demonstrate significant improvements in user behavior prediction compared to state-of-the-arts. |
| Tasks | Recommendation Systems |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6480-coevolutionary-latent-feature-processes-for-continuous-time-user-item-interactions |
| http://papers.nips.cc/paper/6480-coevolutionary-latent-feature-processes-for-continuous-time-user-item-interactions.pdf | |
| PWC | https://paperswithcode.com/paper/coevolutionary-latent-feature-processes-for |
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Agnostic Estimation for Misspecified Phase Retrieval Models
| Title | Agnostic Estimation for Misspecified Phase Retrieval Models |
| Authors | Matey Neykov, Zhaoran Wang, Han Liu |
| Abstract | The goal of noisy high-dimensional phase retrieval is to estimate an $s$-sparse parameter $\boldsymbol{\beta}^*\in \mathbb{R}^d$ from $n$ realizations of the model $Y = (\boldsymbol{X}^{\top} \boldsymbol{\beta}^*)^2 + \varepsilon$. Based on this model, we propose a significant semi-parametric generalization called misspecified phase retrieval (MPR), in which $Y = f(\boldsymbol{X}^{\top}\boldsymbol{\beta}^*, \varepsilon)$ with unknown $f$ and $\operatorname{Cov}(Y, (\boldsymbol{X}^{\top}\boldsymbol{\beta}^*)^2) > 0$. For example, MPR encompasses $Y = h(\boldsymbol{X}^{\top} \boldsymbol{\beta}^*) + \varepsilon$ with increasing $h$ as a special case. Despite the generality of the MPR model, it eludes the reach of most existing semi-parametric estimators. In this paper, we propose an estimation procedure, which consists of solving a cascade of two convex programs and provably recovers the direction of $\boldsymbol{\beta}^*$. Our theory is backed up by thorough numerical results. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6094-agnostic-estimation-for-misspecified-phase-retrieval-models |
| http://papers.nips.cc/paper/6094-agnostic-estimation-for-misspecified-phase-retrieval-models.pdf | |
| PWC | https://paperswithcode.com/paper/agnostic-estimation-for-misspecified-phase |
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