Latent Dirichlet Allocation (LDA) is a fully generative approach to language modelling which overcomes the inconsistent generative semantics of Probabilistic Latent Semantic Index...
Non-negative Matrix Factorization (NMF) and Probabilistic Latent Semantic Indexing (PLSI) have been successfully applied to document clustering recently. In this paper, we show th...
Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...