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Affinity and Penalty Jointly Constrained Spectral Clustering With All-Compatibility, Flexibility, and Robustness
The existing, semisupervised, spectral clustering approaches have two major drawbacks, i.e., either they cannot cope with multiple categories of supervision or they sometimes exhibit unstable effectiveness. To address these issues, two normalized affinity and penalty jointly constrained spectral clu...
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| Pubblicato in: | IEEE Trans Neural Netw Learn Syst |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4990515/ https://ncbi.nlm.nih.gov/pubmed/26915134 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TNNLS.2015.2511179 |
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