.png){kind=icon}
Return
Regularized matrix completion with partial side information
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2019.12.021.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Side information has been shown useful for improving the performance of matrix completion applications. However, in most cases, only partial side information of either the column or row space is available. In this work, we propose a novel regularization based model to incorporate partial side information in matrix completion. We provide theoretical guarantees to ensure the success of the proposed model. It is proved that the proposed model achieves the state-of-the-art sample complexity when the given partial side information is exact, and an error bound for inexact partial side information is also provided. Moreover, we provide a deterministic rule for the selection of regularization parameter. We conduct extensive experiments on both synthetic and real-world data-sets. Experimental results show that our model succeeds to incorporate partial side information, and outperforms the state-of-the-art models on most data-sets. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Matrix completion
Side information
Prior subspace information
Regularization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveNatural Regulatory T Cells Control Coronary Arteriolar Endothelial Dysfunction in Hypertensive Mice
OAAI
OAAIShareSave
View more