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Sparse low-rank separated representation models for learning from data
We consider the problem of learning a multivariate function from a set of scattered observations using a sparse low-rank separated representation (SSR) model. The model structure considered here is promising for high-dimensional learning problems; however, existing training algorithms based on alter...
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| Veröffentlicht in: | Proc Math Phys Eng Sci |
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| Hauptverfasser: | , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
The Royal Society Publishing
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6364613/ https://ncbi.nlm.nih.gov/pubmed/30760956 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rspa.2018.0490 |
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