Distributed Matrix Factorization
Distributed Matrix Factorization is a computational framework within the class of matrix factorization methods that is distinguished by its design to partition and process large-scale matrices across multiple computing nodes, enabling scalable and parallelized decomposition through distributed memory and coordinated computation.
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3.7K
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237
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119
Institutions
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2017–2026
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Distributed large-scale natural graph factorization
Amr Ahmed, Nino Shervashidze, Shravan Narayanamurthy et al. · 2013 · 678 citations
Large-scale matrix factorization with distributed stochastic gradient descent
Rainer Gemulla, Erik Nijkamp, Peter J. Haas et al. · 2011 · 619 citations
Distributed estimation of principal eigenspaces
Jianqing Fan, Dong Wang, Kaizheng Wang et al. · The Annals of Statistics · 2019 · 149 citations · Full text
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Carnegie Mellon University
Pittsburgh, United States
5 h-index
15 publications
1.6K citations
Google (United States)
Mountain View, United States
4 h-index
5 publications
1.4K citations
Princeton University
Princeton, United States
3 h-index
9 publications
737 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
3 h-index
3 publications
728 citations
Yahoo (United States)
Sunnyvale, United States
3 h-index
5 publications
130 citations
Seoul National University
Seoul, South Korea
3 h-index
5 publications
227 citations
IBM Research - Almaden
San Jose, United States
3 h-index
6 publications
2K citations

Zhejiang University
Hangzhou, China
3 h-index
5 publications
106 citations
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Repository · 7 publications · 233 citations
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TKDE · 2 publications · 28 citations
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2 publications · 73 citations
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TKDD · 2 publications · 23 citations
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2 publications · 42 citations
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