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...
Main Authors: | , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
Springer US
2023
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Online Access: | https://hdl.handle.net/1721.1/152104 |