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Regularized matrix completion with partial side information

delete2020-03-01
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PRE
AI
K
Kefu Yi *
胡宏伟 封面图
胡宏伟 (Hongwei Hu)
Y
Yang Yu
郝
郝威 (Wei Hao)
DOI:10.1016/j.neucom.2019.12.021delete
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摘要

摘要

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.
Keyword:
Matrix completion
Side information
Prior subspace information
Regularization
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期刊

Neurocomputing 封面图
Neurocomputing
IF:
6.5
论文数:
2.5W
被引数:
6.5W

机构

U
university of technology sydney
学者数:
1.6W
论文数: 2.0W
被引数: 25
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