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How to Handle Small Samples: Bootstrap and Bayesian Methods in the Analysis of Linguistic Change

A. Hinneburg, H. Mannila, S. Kaislaniemi, T. Nevalainen, H. Raumolin-Brunberg
2006 Literary and Linguistic Computing  
Bootstrap and Bayesian methods provide techniques for handling the uncertainty in small samples.  ...  We describe these techniques for estimating frequencies from small samples, and show how they can be applied to the study of linguistic change. As a test case,  ...  Acknowledgements The research carried out for this article by S.K., T.N. and H.R.-B. was supported by the Academy of Finland Centre of Excellence funding for the VARIENG Research Unit.  ... 
doi:10.1093/llc/fqm006 fatcat:achligkoh5dmbj2cl6uwiucizu

Bayesian computation: a perspective on the current state, and sampling backwards and forwards [article]

Peter J. Green , Marcelo Pereyra, Christian P. Robert (Paris-Dauphine and Warwick)
2015 arXiv   pre-print
The difficulties of modelling and then handling ever more complex datasets most likely call for a new type of tool for computational inference that dramatically reduce the dimension and size of the raw  ...  In Bayesian inference, first and foremost, MCMC techniques continue to evolve, moving from random walk proposals to Langevin drift, to Hamiltonian Monte Carlo, and so on, with both theoretical and algorithmic  ...  Bayesian computation began in order to answer rather practical problems -how can we perform a Bayesian analysis of these data using this model?  ... 
arXiv:1502.01148v3 fatcat:hkqwy2o35rf2jgzqpgsoj4uvde

Parsing low-resource languages using Gibbs sampling for PCFGs with latent annotations

Liang Sun, Jason Mielens, Jason Baldridge
2014 Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)  
We show that a Gibbs sampling technique is capable of parsing sentences in a wide variety of languages and producing results that are on-par with or surpass previous approaches.  ...  Our results for Kinyarwanda and Malagasy in particular demonstrate that low-resource language parsing can benefit substantially from a Bayesian approach.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of the U.S. Army Research Office.  ... 
doi:10.3115/v1/d14-1035 dblp:conf/emnlp/SunMB14 fatcat:t7benewcmrdqzmvskzto2tksia

Bayesian computation: a summary of the current state, and samples backwards and forwards

Peter J. Green, Krzysztof Łatuszyński, Marcelo Pereyra, Christian P. Robert
2015 Statistics and computing  
In Bayesian inference, first and foremost, MCMC techniques have continued to evolve, moving from random walk proposals to Langevin drift, to Hamiltonian Monte Carlo, and so on, with both theoretical and  ...  The difficulties of modelling and then handling ever more complex datasets most likely call for a new type of tool for computational inference that dramatically reduces the dimension and size of the raw  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s11222-015-9574-5 fatcat:mdlw3fdtvjfkxjyo2ivgwdv4oe

Sampling Tree Fragments from Forests

Tagyoung Chung, Licheng Fang, Daniel Gildea, Daniel Štefankovič
2014 Computational Linguistics  
We study the problem of sampling trees from forests, in the setting where probabilities for each tree may be a function of arbitrarily large tree fragments.  ...  In this application, the forests being sampled represent the set of Hiero-style rules that are consistent with fixed input word-level alignments.  ...  , LDC2006E34, LDC2006E85, LDC2006E92, LDC2006E24, LDC2006E92, LDC2006E24) The language model is trained on the English side of entire data (1.65M sentences, which is 39.3M words.)  ... 
doi:10.1162/coli_a_00170 fatcat:slvirjjyjbcrxjm66i3zklv7l4

Psychometric evaluation of the canine brief pain inventory in a Swedish sample of dogs with pain related to osteoarthritis

Ann Essner, Lena Zetterberg, Karin Hellström, Pia Gustås, Hans Högberg, Rita Sjöström
2017 Acta Veterinaria Scandinavica  
However, based on the confirmatory factor analysis, the original factor structure in the CBPI is not ideally suited to measure pain related to OA in our sample and the hypothesis of the presented twofactor  ...  Confirmatory factor analysis was not able to confirm the factor-structure models tested in our sample.  ...  Acknowledgements We are grateful to the dogs and their owners who participated in this study.  ... 
doi:10.1186/s13028-017-0311-2 pmid:28668080 pmcid:PMC5493851 fatcat:qeij4y4hxnah7hs2eiic3iy3ei

Tutorial on Computational Linguistic Phylogeny

Johanna Nichols, Tandy Warnow
2008 Language and Linguistics Compass  
This tutorial surveys the different methods and different types of linguistic data that have been used to estimate phylogenies, explains the scientific and mathematical foundations of phylogenetic estimation  ...  Over the last 10 or more years, there has been a tremendous increase in the use of computational techniques (many of which come directly from biology) for estimating evolutionary histories (i.e., phylogenies  ...  Short Biographies Johanna Nichols is Professor of Slavic Languages and Literatures and Affiliate Professor of Linguistics at the University of California, Berkeley.  ... 
doi:10.1111/j.1749-818x.2008.00082.x fatcat:n6dkjfv7fza6zeog6xe3pjsbra

Indo-European phylogenetics with R

David Goldstein
2020 Indo-European Linguistics  
I discuss the strengths and weaknesses of each of these methods and in addition explicate various measures associated with phylogenetic estimation, including homoplasy indices and bootstrapping.  ...  The last twenty or so years have witnessed a dramatic increase in the use of computational methods for inferring linguistic phylogenies.  ...  Finally, computational methods-in particular maximum likelihood estimation and Bayesian inference-enable historical linguists to infer phylogenies based on specific models of linguistic change (known as  ... 
doi:10.1163/22125892-20201000 fatcat:ipzgfnqr4rhyjlkfmzlgvrn2jy

Sampling and Ontologically Pooling Web Images for Visual Concept Learning

Shiai Zhu, Chong-Wah Ngo, Yu-Gang Jiang
2012 IEEE transactions on multimedia  
For the former, a simple method named semantic field is introduced to handle the imprecise and incomplete image tags.  ...  To boost the coverage or diversity of the training sets, we further propose an ontology-based hierarchical pooling method to collect samples not only based on the target concept alone, but also from ontologically  ...  Under our application, a tag list can be treated as a SF, where the dominant semantics can be inferred by linguistic analysis of the tags.  ... 
doi:10.1109/tmm.2012.2190387 fatcat:bimponlnoze6lk7ofhd6xuwq3a

Integration of Multiple Bilingually-Trained Segmentation Schemes into Statistical Machine Translation

Michael PAUL, Andrew FINCH, Eiichiro SUMITA
2011 IEICE transactions on information and systems  
In the first step, an iterative bootstrap method is applied to learn multiple segmentation schemes that are consistent with the phrasal segmentations of an SMT system trained on the resegmented bitext.  ...  The method can be applied to any language pair in which the source language is unsegmented and the target language segmentation is known.  ...  Acknowledgements This work is partly supported by the Grant-in-Aid for Scientific Research (C) Number 19500137.  ... 
doi:10.1587/transinf.e94.d.690 fatcat:jjimxygdpnbihbkex3rreuzicy

Statistically Significant Detection of Linguistic Change [article]

Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, Steven Skiena
2014 arXiv   pre-print
We propose a new computational approach for tracking and detecting statistically significant linguistic shifts in the meaning and usage of words.  ...  Our meta-analysis approach constructs property time series of word usage, and then uses statistically sound change point detection algorithms to identify significant linguistic shifts.  ...  Acknowledgments We thank Andrew Schwartz for providing us access to the Twitter stream data and for insightful discussions.  ... 
arXiv:1411.3315v1 fatcat:hrfbd4qe6ra3nk7ydceewzi4qi

The Uses of Machine Learning (ML) in Teaching and Learning English Language: A Methodical Review

Abdullah AbdulMuhsen AlHarbi
2022 Journal of Education  
The current research employed a mixed-methods approach (approach) that included qualitative and quantitative analysis to survey the previous studies on machine learning in EFL/ESL instruction.  ...  Consequently, the current study sought to perform a systematic review of the research that revealed numerous applications of machine learning (ML) in English language instruction (Applied Linguistics)  ...  According to the facts offered above, Bayesian analysis has been used in L2 study by linguists to make decisions.  ... 
doi:10.21608/edusohag.2022.212355 fatcat:icfe34jourgkphea6fl63xil3u

Statistically Significant Detection of Linguistic Change

Vivek Kulkarni, Rami Al-Rfou, Bryan Perozzi, Steven Skiena
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15  
We propose a new computational approach for tracking and detecting statistically significant linguistic shifts in the meaning and usage of words.  ...  Our meta-analysis approach constructs property time series of word usage, and then uses statistically sound change point detection algorithms to identify significant linguistic shifts.  ...  Acknowledgments We thank Andrew Schwartz for providing us access to the Twitter data.  ... 
doi:10.1145/2736277.2741627 dblp:conf/www/KulkarniAPS15 fatcat:oz5vpfwcfvdgjgit2h3x5l32qa

Probabilistic models of language processing and acquisition

Nick Chater, Christopher D. Manning
2006 Trends in Cognitive Sciences  
Probabilistic methods are providing new explanatory approaches to fundamental cognitive science questions of how humans structure, process and acquire language.  ...  Language comprehension and production involve probabilistic inference in such models; and acquisition involves choosing the best model, given innate constraints and linguistic and other input.  ...  Christopher Manning was supported in part by the Advanced Research and Development Activity (ARDA)'s AQUAINT Program and by an IBM Faculty Partnership Award.  ... 
doi:10.1016/j.tics.2006.05.006 pmid:16784883 fatcat:uqsmsgbt2jbuhfaw4a52kkgoke

Count Data Analysis in Randomised Clinical Trials

Jakobsen JC Tamborrino M
2015 Journal of Biometrics & Biostatistics  
We focus on analysis of simple count data and do not consider methods for analyzing longitudinal count data or Bayesian statistical analysis.  ...  In this paper, we review count data analysis with different parametric and non-parametric methods used in randomised clinical trials, and we define procedures for choosing between the two methods and their  ...  Acknowledgement We thank Dimitrinka Nikolova for her patient copyediting and linguistic suggestions. JCJ, JW, PW, and CG were partly funded by The Copenhagen Trial Unit.  ... 
doi:10.4172/2155-6180.1000227 fatcat:olpmlmeft5fzxfnn5m5u2hzu6q
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