Two-dimensional data partitioning for non-negative matrix tri-factorization
As a two-sided clustering and dimensionality reduction paradigm, Non-negative Matrix Tri-Factorization (NMTF) has attracted much attention in machine learning and data mining researchers due to its excellent performance and reliable theoretical support. Unlike Non-negative Matrix Factorization (NMF)...
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| Published in: | Big data research Vol. 37; p. 100473 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
28.08.2024
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| Subjects: | |
| ISSN: | 2214-5796, 2214-580X |
| Online Access: | Get full text |
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