... sampling; **Latent** **variable** mod- els; Marginal distribution; Mean-field variational methods 1 Introduction Bayesian inference typically requires the computation of the posterior distribution for a collection ...

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... Multivariate **latent** **variable** statistical methods such as principal component analysis (PCA) and projection to **latent** structures (PLS) were use to analyse the image ...

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... on **latent** Dirichlet allocation (LDA, Blei et ...deep **latent** **variable** model for both the ordinal matrix encoding the user/product scores, and the document-term matrix en- coding the ...

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... ABSTRACT **Latent** **variable** models in finance originate both from asset pricing theory and time series ...of **latent** structures, which are both useful to reduce the dimension of a statistical model ...

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... **Latent** **variable** models in finance originate both from asset pricing theory and time series ...of **latent** structures, which are both useful to reduce the dimension of a statistical model specified for ...

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... VI. DISCUSSION I have proposed a reformulation of the Ising distribu- tion as a **latent** **variable** model, and used it to derive prin- cipled approximations by the simpler Cox distribution. In practical ...

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... ABSTRACT **Latent** **variable** models in finance originate both from asset pricing theory and time series ...of **latent** structures, which are both useful to reduce the dimension of a statistical model ...

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... the **latent** **variable**. However, the **latent** **variable** has limited capacity, and may model only the aspects that contribute to most of the reconstruction loss (abstract concepts) and there may be ...

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... Learning **latent** **variable** models, such as clustering terrains in a feature space, is a difficult ...of **latent** surfaces representing the data and this translated into accurate ...

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... their corresponding rating 𝑦(𝑢, 𝑖) is a noisy measurement of 𝑓 (𝑥 1 (𝑢), 𝑥 2 (𝑖)) for some unknown function 𝑓 . In contrast to classical regression, the features 𝑥 = (𝑥 1 (𝑢), 𝑥 2 (𝑖)) are not observed (**latent**), ...

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... to **Latent** Structure (PLS) ...to **Latent** Structures (PLS) regression was also used to correlate acousto-ultrasonic features and textural descriptors collected from corresponding X-ray CT-Scan ...

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... The Present Study To date, no studies have explored the **latent** structure of RAN and whether one or several RAN factors are needed to predict academic outcomes, such as reading and arithmetic. Investigating this ...

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... The **latent** factors z of the model can be seen as topics that are present in the data. The parameters of each topic can be used as descriptions of the topic. P (t|z) represents the probabilities of the terms for ...

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... observed **variable** and a target **variable** such as the phenotype, conditional on the **latent** **variable**, parent of the observed ...phenotype **variable** is not included in the ...

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... a **latent** **variable** is mainly therapeutic rather than ...hidden **variable** is often seen as a therapeutic target rather than an etiological node; that is, not something to find that would explain ...

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... **Latent** **variable** Gibbs sampler 1. Generate Z i ( i = 1 ;:::;n ) from (4), 2. Generate j ( j = 1 ;:::;k ) from (3). This sampler is quite easy to implement, retaining an iid structure in each iteration, and ...

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... plete **latent** **variable** decomposition of counts data. In Neural Information Processing Systems, Vancouver, BC, Canada, December 2007. [10] Paris Smaragdis and Judith C. Brown. Non-negative matrix ...

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... particular **Latent** Dirichlet Allocation (LDA) [5] model to decentralized ...for **latent** **variable** models, which adapts online EM [7] with local Gibbs sampling in the case of intractable **latent** ...

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... GAZE **LATENT** SUPPORT VECTOR MACHINE FOR IMAGE CLASSIFICATION Xin Wang Nicolas Thome Matthieu Cord Sorbonne Universit´es, UPMC Univ Paris 06, UMR 7606, LIP6, F-75005, Paris, France This paper deals with image ...

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... to **latent** **variable** models of independent ...Keywords: **Latent** data models, Expectation-Maximisation, adaptive algorithms, online estima- tion, stochastic approximation, Polyak-Ruppert averaging, ...

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