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Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion [PDF]
In this paper, we develop a relative error bound for nuclear norm regularized matrix completion, with the focus on the completion of full-rank matrices.
Yang, Tianbao +3 more
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, 2019 International audienceMatrix completion aims to reconstruct a data matrix based on observations of a small number of its entries. Usually in matrix completion a single matrix is considered, which can be, for example, a rating matrix in recommendation ...
Klopp, Olga, Alaya, Mokhtar Z.
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Matrix Completion by Deep Matrix Factorization
Neural Networks, 2018Conventional methods of matrix completion are linear methods that are not effective in handling data of nonlinear structures. Recently a few researchers attempted to incorporate nonlinear techniques into matrix completion but there still exists considerable limitations.
Jicong Fan, Jieyu Cheng
exaly +3 more sources
Colorization by Matrix Completion
Proceedings of the AAAI Conference on Artificial Intelligence, 2021Given a monochrome image and some manually labeled pixels, the colorization problem is a computer-assisted process of adding color to the monochrome image. This paper proposes a novel approach to the colorization problem by formulating it as a matrix completion problem.
Shusen Wang, Zhihua Zhang 0008
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2021 IEEE International Symposium on Information Theory (ISIT), 2021
Inspired by real phase retrieval and low-rank matrix recovery, we introduce the problem of unsigned matrix retrieval, where the aim is to recover a matrix of bounded-rank from a sign-ambiguous version of it. Allowing for missing entries in addition to sign ambiguities leads to the problem of unsigned matrix completion.
Yunzhen Yao +2 more
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Inspired by real phase retrieval and low-rank matrix recovery, we introduce the problem of unsigned matrix retrieval, where the aim is to recover a matrix of bounded-rank from a sign-ambiguous version of it. Allowing for missing entries in addition to sign ambiguities leads to the problem of unsigned matrix completion.
Yunzhen Yao +2 more
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Network Completion: Beyond Matrix Completion
2021 International Conference on Information Networking (ICOIN), 2021Due to practical reasons such as limited resources and privacy settings specified by users on social media, most network data tend to be only partially observed with both missing nodes and missing edges. Thus, it is of paramount importance to infer the missing parts of the networks since incomplete network data may severely degrade the performance of ...
Cong Tran, Won-Yong Shin
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2013 IEEE 13th International Conference on Data Mining, 2013
Recovering a matrix from a sampling of its entries is a problem of rapidly growing interest and has been studied under the name of matrix completion. It occurs in many areas of engineering and applied science. In most machine learning and data mining applications, it is possible to leverage the expertise of human oracles to improve the performance of ...
Shayok Chakraborty +5 more
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Recovering a matrix from a sampling of its entries is a problem of rapidly growing interest and has been studied under the name of matrix completion. It occurs in many areas of engineering and applied science. In most machine learning and data mining applications, it is possible to leverage the expertise of human oracles to improve the performance of ...
Shayok Chakraborty +5 more
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2012 IEEE 12th International Conference on Data Mining, 2012
We discuss parallel and distributed algorithms for large-scale matrix completion on problems with millions of rows, millions of columns, and billions of revealed entries. We focus on in-memory algorithms that run on a small cluster of commodity nodes, even very large problems can be handled effectively in such a setup.
Christina Teflioudi +2 more
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We discuss parallel and distributed algorithms for large-scale matrix completion on problems with millions of rows, millions of columns, and billions of revealed entries. We focus on in-memory algorithms that run on a small cluster of commodity nodes, even very large problems can be handled effectively in such a setup.
Christina Teflioudi +2 more
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Optimal Discrete Matrix Completion
Proceedings of the AAAI Conference on Artificial Intelligence, 2016In recent years, matrix completion methods have been successfully applied to solve recommender system applications. Most of them focus on the matrix completion problem in real number domain, and produce continuous prediction values. However, these methods are not appropriate in some occasions where the entries of matrix are discrete ...
Zhouyuan Huo, Ji Liu, Heng Huang 0001
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Deterministic algorithms for matrix completion
Random Structures & Algorithms, 2013ABSTRACTThe goal of the matrix completion problem is to retrieve an unknown real matrix from a small subset of its entries. This problem comes up in many application areas, and has received a great deal of attention in the context of the Netflix challenge. This setup usually represents our partial knowledge of some information domain.
Eyal Heiman +2 more
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