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Found 4 papers, 1 papers with code
Fitting a deeply-nested hierarchical model to a large book review dataset using a moment-based estimator
The main challenge in deploying this model is computational: the data sizes are large, and fitting the model at scale using off-the-shelf maximum likelihood procedures is prohibitive.
Scaling Text with the Class Affinity Model
Probabilistic methods for classifying text form a rich tradition in machine learning and natural language processing.
Profile Likelihood Biclustering
Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset.
Regularized Laplacian Estimation and Fast Eigenvector Approximation
Conversely, it will imply that the solution to this regularized estimation problem can be computed very quickly by running, e. g., the fast diffusion-based PageRank procedure for computing an approximation to the first nontrivial eigenvector of the graph Laplacian.
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