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Found 4 papers, 0 papers with code
Distributed Bayesian Matrix Factorization with Limited Communication
Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals.
Sparse group factor analysis for biclustering of multiple data sources
Motivation: Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes exhibiting consistent patterns over subsets of treatments.
Bayesian multi-tensor factorization
We introduce Bayesian multi-tensor factorization, a model that is the first Bayesian formulation for joint factorization of multiple matrices and tensors.
Group Factor Analysis
Factor analysis provides linear factors that describe relationships between individual variables of a data set.
