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Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
Factor analysis topic model personalized learning machine learning block coordinate descent
2013/6/14
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently developed SPARse Fact...
Sparse Factor Analysis for Learning and Content Analytics
factor analysis sparse probit regression sparse logistic regression Bayesian latent factor analysis personalized learning
2013/4/28
We develop a new model and algorithms for machine learning-based learning analytics, which estimate a learner's knowledge of the concepts underlying a domain, and content analytics, which estimate the...
Order-preserving factor analysis (OPFA)
Order-preserving factor OPFA precedence-ordering optimization
2011/6/17
We present a novel factor analysis method that can be applied to the discovery of common factors shared among trajectories in multivariate time series data. These factors satisfy a precedence-ordering...
Spatial Dynamic Factor Analysis
Bayesian inference forecasting Gaussian process spatial interpolation random fields
2009/9/22
A new class of space-time models derived from standard dynamic fac-
tor models is proposed. The temporal dependence is modeled by latent factors
while the spatial dependence is modeled by the factor...
Expected Posterior Priors in Factor Analysis。
Theoretical Justification of Decision Rules for the Number of Factors: Principal Component Analysis as a Substitute for Factor Analysis in One-Factor Cases
cubic equation greater-than-one rule number of factors principal component analysis representation of a polynomial in terms of a remainder sequence scree test
2009/3/5
Applying principal component analysis as a substitute for factor analysis, we often adopt the following greater-than-one rule to decide the number of factors, k: Take the number of eigenvalues of the ...