Browsing Sentraladministrasjonen by Subject "Tensor decomposition"
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An AO-ADMM Approach to Constraining PARAFAC2 on All Modes
(SIAM Journal on Mathematics of Data Science;Volume 4, Issue 3 | 2022, Peer reviewed; Journal article, 2022-08-30)Analyzing multi-way measurements with variations across one mode of the dataset is a challenge in various fields including data mining, neuroscience and chemometrics. For example, measurements may evolve over time or have ... -
PARAFAC2 AO-ADMM: Constraints in all modes
(European Signal Processing Conference;2021 29th European Signal Processing Conference (EUSIPCO), Conference object, 2021-12-08)The PARAFAC2 model provides a flexible alternative to the popular CANDECOMP/PARAFAC (CP) model for tensor decompositions. Unlike CP, PARAFAC2 allows factor matrices in one mode (i.e., evolving mode) to change across tensor ...