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Low-rank matrix approximation with weights or missing data is NP-hard
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Document type | Document de travail (Working Paper) |
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Access type | Accès libre |
Publication date | 2010 |
Language | Anglais |
Collection | CORE Discussion Paper - 2010/75 |
Affiliations |
UCL
- EUEN/CORE - Center for operations research and econometrics UCL - SST/ICTM/INMA - Pôle en ingénierie mathématique |
Keywords | low-rank matrix approximation ; weighted low-rank approximation ; missing data ; matrix completion with noise ; PCA with missing data ; computational complexity ; maximum-edge biclique problem |
Links |
Bibliographic reference | Gillis, Nicolas ; Glineur, François. Low-rank matrix approximation with weights or missing data is NP-hard. CORE Discussion Paper ; 2010/75 (2010) |
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Permanent URL | http://hdl.handle.net/2078.1/68802 |