19 citations · 33 across the 6 of their papers we have counts for
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math.ST2018★ 9 cited
Variational Approximation Error in Bayesian Non-negative Matrix Factorization
Naoki Hayashi
Non-negative matrix factorization (NMF) is a knowledge discovery method that is used in many fields. Variational inference and Gibbs sampling methods for it are also wellknown. How…
math.ST2017★ 4 cited
Asymptotic Bayesian Generalization Error in Latent Dirichlet Allocation and Stochastic Matrix Factorization
Naoki Hayashi, Sumio Watanabe
Latent Dirichlet allocation (LDA) is useful in document analysis, image processing, and many information systems; however, its generalization performance has been left unknown beca…
math.ST2016★ 19 cited
Upper Bound of Bayesian Generalization Error in Non-negative Matrix Factorization
Naoki Hayashi, Sumio Watanabe
Non-negative matrix factorization (NMF) is a new knowledge discovery method that is used for text mining, signal processing, bioinformatics, and consumer analysis. However, its bas…