Markov Chain Monte Carlo inference for probabilistic latent tensor factorization

Probabilistic Latent Tensor Factorization (PLTF) is a recently proposed probabilistic framework for modeling multi-way data. Not only the popular tensor factorization models but also any arbitrary tensor factorization structure can be realized by the PLTF framework. This paper presents Markov Chain...

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Bibliographische Detailangaben

Hauptverfasser:	Simsekli, U., Cemgil, A. T.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Computational modeling Data models Indexes Markov Chain Monte Carlo (MCMC) Markov processes Monte Carlo methods Probabilistic Latent Tensor Factorization (PLTF) Probabilistic logic Space Alternating Data Augmentation (SADA) Tensile stress
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