Latent variable modeling
Inference and Interpretability in Latent Variable Modeling
... The choice of the appropriate prior is another difficult decision the practitioner has to make. While Supersmooth kernels such as Gaussian kernels give fast density estimation rates (Ghosal and van der Vaart (2001)), ...
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Solving multiplication and division problems: latent variable modeling of students' solution strategies and performance
... not modeling them results in a serious misspecification of the latent class ...that modeling the multilevel effect as nonparametric (cre- ating latent classes of teachers as well as of ...
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Latent Variable Modeling Approach for Assessing Social Impacts of Mine Closure
... Mining stimulates environmental and economic impacts on the neighboring community right from the inception to the closure of its operations. The society in the neighborhood of mining gradually adopts a characteristic ...
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ltm: An R Package for Latent Variable Modeling and Item Response Analysis
... the latent trait model, the three-parameter model, and the graded response model, ...The latent trait model is a general latent variable model for dichotomous data of the form (1), including ...
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Latent variable modeling improves AKI risk factor identification and AKI prediction compared to traditional methods
... continuous variable to enhance AKI discrim- ination and prediction [29, ...evaluate latent variable mixture models with more than two subpopula- tions or perform latent class analysis to ...
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Unsupervised Discovery of Gendered Language through Latent Variable Modeling
... generative latent-variable model that jointly represents adjective (or verb) choice, with its sentiment, given the natural gender of a head (or dependent) ...
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Latent variable modeling and its implications for institutional review board review: variables that delay the reviewing process
... the latent variable of PIs moderated the other latent variable of review, and thus affected ...The latent variables of vulnerability and PIs interacted with review and acted as ...
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Explanatory latent variable modeling of mathematical ability in primary school : crossing the border between psychometrics and psychology
... Therefore, the present study aims at a systematic investigation of the characteristics of mental and written solution strategies Dutch children at the end of primary school use to solve [r] ...
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Latent-Variable Modeling: Algorithms, Inference, and Applications
... observed variable conditioned on the remaining observed variables and latent variables) are distributed as a ...Our modeling ap- proach — parameterized by sparse matrix encoding graph structure among ...
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A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
... language modeling and representation learning ca- ...language modeling results in terms of perplexity but an inferior ELBO value, and we use these results to argue that ELBO is sub- optimal for language ...
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Latent Variable Modeling of String Transductions with Finite State Methods
... with latent classes and no regions, where it accounts for only 30% of the ...or latent regions are used; however, it goes up to 27% if both latent classes and regions are ...
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Latent Variable Models for Semantic Orientations of Phrases
... In the proposed models, only the words that ap- peared in the training dataset can be classified. An attempt to deal with the unseen words is an in- teresting task. For example, we could extend our models to ...
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Probabilistic Distributional Semantics with Latent Variable Models
... a latent HMM state conditioned on the preceding word’s state; Moon, Erk, and Baldridge (2010) show that combining HMM and LDA components can improve unsupervised part-of-speech ...
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A Comparison of Latent Variable Models For Conversation Analysis
... We present a novel method of modeling discourse using an exponential state Hidden Markov Model where states are based on speakers and addressees.. We also cast the problem into the popul[r] ...
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A Latent Variable Model for Geographic Lexical Variation
... An active recent literature concerns geotagged in- formation on the web, such as search queries (Back- strom et al., 2008) and tagged images (Crandall et al., 2009). This research identifies the geographic distribution ...
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Experiments with Spectral Learning of Latent Variable PCFGs
... Latent-variable PCFGS (L-PCFGs) are a highly suc- cessful model for natural language parsing (Mat- suzaki et al., 2005; Petrov et al., 2006). Recent work (Cohen et al., 2012) has introduced a spectral ...
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A dynamic latent variable model for source separation
... novel latent variable model for learning latent bases for time-varying non-negative ...Dirichlet latent variable model (dynamic DLVM) to the two popular latent basis learning ...
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Latent Variable Synchronous CFGs for Hierarchical Translation
... learn latent refinements of single-category syn- chronous grammars, so as to improve translation ...this latent-variable model: one based on EM and the other is a spec- tral algorithm based on the ...
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Latent variable models for binary response data
... in latent variable models, since they involve observable (manifest) variables and not directly observable (latent) variables which corresponds to a case of incomplete data, as defined by Dempster, ...
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SILVar: Single Index Latent Variable Models
... of latent variables, which manifest as unmodeled trends in the ...Index Latent Variable (SILVar) model, which uses the SIM in a sparse plus low-rank optimization setting to enable general, ...
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