A Novel Correlation-Based CUR Matrix Decomposition Method

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Hemmati Arash; Nasiri Hamid; AMIRHAERI MARYAM; Ebadzadeh Mohammad Mehdi

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2020 | Issue:6

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Title

A Novel Correlation-Based CUR Matrix Decomposition Method

Author(s)

Hemmati Arash | Nasiri Hamid | AMIRHAERI MARYAM | Ebadzadeh Mohammad Mehdi

Keywords

CUR Matrix Decomposition

High-Dimensional Data

Low-Rank Approximations

Singular Value Decomposition

Abstract

Web data such as documents, images, and videos are examples of large matrices. To deal with such matrices, one may use matrix decomposition techniques. As such, CUR Matrix Decomposition is an important approximation technique for High-Dimensional Data. It approximates a data matrix by selecting a few of its rows and columns. However, a problem faced by most CUR decomposition matrix methods is that they ignore the correlation among columns (rows), which gives them lesser chance to be selected; even though, they might be appropriate candidates for basis vectors. In this paper, a novel CUR Matrix Decomposition method is proposed, in which calculation of the correlation, boosts the chance of selecting such columns (rows). Experimental results indicate that in comparison with other methods, this one has had higher accuracy in matrix approximation.

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APA: Copy

Hemmati, Arash, Nasiri, Hamid, AMIRHAERI, MARYAM, & Ebadzadeh, Mohammad Mehdi. (2020). A Novel Correlation-Based CUR Matrix Decomposition Method. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949244/en

Vancouver: Copy

Hemmati Arash, Nasiri Hamid, AMIRHAERI MARYAM, Ebadzadeh Mohammad Mehdi. A Novel Correlation-Based CUR Matrix Decomposition Method. 2020. Available from: https://sid.ir/paper/949244/en

IEEE: Copy

Arash Hemmati, Hamid Nasiri, MARYAM AMIRHAERI, and Mohammad Mehdi Ebadzadeh, “A Novel Correlation-Based CUR Matrix Decomposition Method,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2020, [Online]. Available: https://sid.ir/paper/949244/en

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