Results 31 to 40 of about 2,998,558 (396)
Deep Impact: Unintended consequences of journal rank
Frontiers in Human Neuroscience, 2013 Most researchers acknowledge an intrinsic hierarchy in the scholarly journals (‘journal rank’) that they submit their work to, and adjust not only their submission but also their reading strategies accordingly.
Björn eBrembs +2 more
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Hierarchical relational models for document networks [PDF]
, 2010 We develop the relational topic model (RTM), a hierarchical model of both network structure and node attributes. We focus on document networks, where the attributes of each document are its words, that is, discrete observations taken from a fixed ...
Blei, David M., Chang, Jonathan
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Topics in statistical mechanics [PDF]
, 1984 This thesis deals with four independent topics in statistical mechanics: (1) the dimer problem is solved exactly for a hexagonal lattice with general boundary using a known generating function from the theory of partitions. It is shown that the leading term in the entropy depends on the shape of the boundary; (2) continuum models of percolation and ...
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Frontiers in Neurology, 2018 The use of high-dose methylprednisolone for acute spinal cord injury continues to be a topic of debate. This controversy largely stems from fundamental issues in statistical interpretation of trial data, most notably subgroup analyses.
Shannon Hextrum, Stephanie Bennett
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Problem-Driven Teaching: Estimating the Population from a Sample
Computer Sciences & Mathematics Forum, 2023 Today, mathematics teachers are realizing that there are many benefits of problem-driven teaching, but also face a number of challenges, such as a lack of confidence, not knowing how to design high-quality problems, and not knowing how to deal with the ...
Guoqiang Dang +3 more
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Topic-Based Influence Computation in Social Networks under Resource Constraints [PDF]
, 2018 As social networks are constantly changing and evolving, methods to analyze dynamic social networks are becoming more important in understanding social trends.
Bingöl, Kaan +4 more
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Anchor-Free Correlated Topic Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 In topic modeling, identifiability of the topics is an essential issue. Many topic modeling approaches have been developed under the premise that each topic has a characteristic anchor word that only appears in that topic.
Xiao Fu +4 more
semanticscholar +1 more source
Spatial Data in Undergraduate Statistics Curriculum
Journal of Statistics and Data Science Education, 2021 In this article we present and discuss the importance and relevance of the inclusion of spatial data analysis as part of the undergraduate statistics curriculum.
Nicolas Christou
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Uncertainty-aware Topic Modeling Visualization [PDF]
arXiv, 2021 Topic modeling is a state-of-the-art technique for analyzing text corpora. It uses a statistical model, most commonly Latent Dirichlet Allocation (LDA), to discover abstract topics that occur in the document collection. However, the LDA-based topic modeling procedure is based on a randomly selected initial configuration as well as a number of parameter
arxiv
Topics in statistical machine translation [PDF]
Tutorial Abstracts of ACL-IJCNLP 2009 on - ACL-IJCNLP '09, 2009 In the past, we presented tutorials called "Introduction to Statistical Machine Translation", aimed at people who know little or nothing about the field and want to get acquainted with the basic concepts. This tutorial, by contrast, goes more deeply into selected topics of intense current interest. We aim at two types of participants: 1.
Kevin Knight, Philipp Koehn
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