In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
Background: The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of m...
David M. Blei, K. Franks, Michael I. Jordan, I. Sa...