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Latent variable
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#	Item
21	Exploring the measurement profiles of socioeconomic background indicators and their differences in reading achievement: A two-level latent class analysis Kajsa Yang Hansen and Ingrid Munck Add to Reading List Source URL: ierinstitute.org Language: English - Date: 2012-09-07 05:53:57 Statistics Psychometrics Statistical models Categorical data Structural equation models Econometric modeling Latent class model Socioeconomic status Latent variable Intelligence quotient Structural equation modeling Latent variable model
22	NBER WORKING PAPER SERIES DSGE MODELS IN A DATA-RICH ENVIRONMENT Jean Boivin Marc Giannoni Working Paper 12772 Add to Reading List Source URL: faculty.wcas.northwestern.edu Language: English - Date: 2007-05-02 20:13:16 Economics Macroeconomics New classical macroeconomics New Keynesian economics Dynamic stochastic general equilibrium Macroeconomic model Psychometrics Real business-cycle theory Economic model Latent variable Statistics Structural estimation
23	CS 3750 Machine Learning Latent variable models Variational approximations. Milos Hauskrecht Add to Reading List Source URL: people.cs.pitt.edu Language: English - Date: 2014-10-25 10:58:54 Statistics Statistical theory Probability distributions Estimation theory Expectationmaximization algorithm Missing data Normal distribution Likelihood-ratio test Variational Bayesian methods KullbackLeibler divergence
24	Journal of Machine Learning Research) ?? Submitted ??; Published ?? Posterior Regularization for Structured Latent Variable Models Kuzman Ganchev Add to Reading List Source URL: www.seas.upenn.edu Language: English - Date: 2011-02-28 22:52:31 Statistics Estimation theory Statistical theory Expectationmaximization algorithm Maximum likelihood estimation KullbackLeibler divergence Sufficient statistic Likelihood function Gamma distribution Generalized coordinates
25	Are Things Really Getting Better?: How To Validate Latent Variable Models of Human Rights Christopher J. Fariss∗† Abstract Has respect for human rights improved? Answering this question requires valid comparisons of Add to Reading List Source URL: cfariss.com Language: English - Date: 2016-06-23 14:00:50 Statistics Statistical models Psychometrics Statistical methods Latent variable model Latent variable Human rights Latency Regression analysis
26	Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development Diane J. Hu1 , Laurens van der Maaten1,2 , Youngmin Cho1 , Lawrence K. Saul1 , Sorin Lerner1 1 Dept. of Computer Science & Engin Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Software Probability Statistics Archive formats Dimension reduction Principal component analysis Mixture model Apache Subversion Markov chain Restricted Boltzmann machine Version control Tar
27	JMLR: Workshop and Conference Proceedings vol 40:1–77, 2015 Learning Overcomplete Latent Variable Models through Tensor Methods Animashree Anandkumar Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:35 Algebra Mathematics Machine learning Linear algebra Statistical models Signal processing Multivariate statistics Higher-order singular value decomposition Independent component analysis Tensor Feature learning Unsupervised learning
28	Learning Latent Groups with Hinge-loss Markov Random Fields Stephen H. Bach Bert Huang Lise Getoor University of Maryland, College Park, Maryland 20742, USA Add to Reading List Source URL: stephenbach.net Language: English - Date: 2013-06-14 15:37:03 Statistics Probability theory Graphical models Machine learning Statistical models Statistical theory Bayesian statistics Markov random field Latent variable Expectationmaximization algorithm Marginal likelihood Conditional random field
29	Author manuscript, published in "International Conference on Information Processing in Medical Imaging (2013)" Learning from M/EEG data with variable brain activation delays Wojciech Zaremba1,2 , M. Pawan Kumar1,2,3 , A Add to Reading List Source URL: cs.nyu.edu Language: English - Date: 2013-09-17 23:46:03 Statistics Statistical models Neuroscience Bayesian networks Statistical classification Support vector machine Electroencephalography Latent variable Data analysis
30	TEDS-M: Diagnosing teacher knowledge by applying multidimensional item response theory and multiple-group models Sigrid Blömeke Humboldt University of Berlin, Berlin, Germany Add to Reading List Source URL: ierinstitute.org Language: English - Date: 2012-01-04 07:01:18 Psychometrics Statistics Psychology Education Item response theory Rasch model Factor analysis Measurement invariance Differential item functioning Scale G factor Latent variable model