The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf
.
Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis
[article]
2012
arXiv
pre-print
Tensor decomposition is a powerful computational tool for multiway data analysis. Many popular tensor decomposition approaches---such as the Tucker decomposition and CANDECOMP/PARAFAC (CP)---amount to multi-linear factorization. They are insufficient to model (i) complex interactions between data entities, (ii) various data types (e.g. missing data and binary data), and (iii) noisy observations and outliers. To address these issues, we propose tensor-variate latent nonparametric Bayesian
arXiv:1108.6296v2
fatcat:5lmkluhoundudjt63a6mnr6jne