Tensor completion with noisy side information

Abstract We develop a new model for tensor completion which incorporates noisy side information available on the rows and columns of a 3-dimensional tensor. This method learns a low rank representation of the data along with regression coefficients for the observed noisy features. Given...

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Bibliographic Details
Main Authors: Bertsimas, Dimitris, Pawlowski, Colin
Other Authors: Massachusetts Institute of Technology. Operations Research Center
Format: Article
Language:English
Published: Springer US 2023
Online Access:https://hdl.handle.net/1721.1/152104