Missing data can be informative. Ignoring this information lead to misleading conclusions when the model does not allow extracted from missing data. We propose a co-clustering model, based on binary Latent Block Model, that aims take advantage of nonignorable nonresponses, also known as Not At Random A variational expectation–maximization algorithm is derived perform inference and selection cri...

Correctly choosing the number of topics plays an important role in successfully applying topic models to real world applications. Following the latest tensor decomposition framework by Anandkumar et al., we make the first attempt to provide theoretical analysis on the number of topics under Latent Dirichlet Allocation model. With mild conditions, our method provides accessible information on th...

Demonstrates methods of detecting local dependence in binary data latent class models. Latent class models are applied to five repeated measures of voter turnout in the Dutch Parliamentary elections of 2006 and 2010 obtained from a probability sample of 9510 citizens. Modeling substantive local dependence as separate discrete latent variables while modeling nuisance dependencies as direct effec...

Finding latent factors of the data using matrix factorizations is a tried-and-tested approach in data mining. But finding shared factors over multiple matrices is more novel problem. Specifically, given two matrices, we want to find a set of factors shared by these two matrices and sets of factors specific for the matrices. Not only does such decomposition reveal what is common between the two ...

Video editing is the process of selecting and joining various fragments of video material (called shots) to create a final video sequence. In an editing process, there are many possible ways to make a transition from one shot to another. So, the quality of a created video depends on the editor’s skills, that is, the quality of the video created by professional editors is much higher than that o...