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LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values
Binary data with one-class missing values are ubiquitous in real-world applications. They can be represented by irregular tensors with varying sizes in one dimension, where value one means presence of a feature while zero means unknown (i.e., either presence or absence of a feature). Learning accura...
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| Publicat a: | KDD |
|---|---|
| Autors principals: | , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8186437/ https://ncbi.nlm.nih.gov/pubmed/34109054 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1145/3394486.3403213 |
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