Divide-and-conquer approach for solving singular value decomposition based on MapReduce

Author:

Zhao Shuoyi1,Li Ruixuan1,Tian Wenlong2,Xiao Weijun3,Dong Xinhua1,Liao Dongjie1,Khan Samee U.4,Li Keqin5

Affiliation:

1. School of Computer Science and Technology; Huazhong University of Science and Technology; Wuhan Hubei 430074 China

2. School of Software Engineering; Huazhong University of Science and Technology; Wuhan Hubei 430074 China

3. Department of Electrical and Computer Engineering; Virginia Commonwealth University; Richmond VA 23284 USA

4. Department of Electrical and Computer Engineering; North Dakota State University; Fargo ND 58108 USA

5. Department of Computer Science; State University of New York-New Paltz; New Paltz, New York NY 12561 USA

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference28 articles.

1. Singular value decomposition http://en.wikipedia.org/wiki/Singular_value_decomposition

2. Dean J Ghemawat S MapReduce: simplified data processing on large clusters Operating Systems Design and Implementation San Francisco, California 2004 137 150

3. Mahout http://mahout.apache.org

4. Bayramli B SVD Factorization for tall-and-fat matrices on Map/Reduce architectures 2013

5. Numerical solution of a secular equation;Melman;Numerische Mathematik,1995

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1. Density estimation-based method to determine sample size for random sample partition of big data;Frontiers of Computer Science;2023-12-16

2. Shadow: Exploiting the Power of Choice for Efficient Shuffling in MapReduce;2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS);2017-12

3. Advances in modelling and simulation for big-data applications (AMSBA);Concurrency and Computation: Practice and Experience;2016-01-09

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