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Learning Kernels for variants of Normalized Cuts: Convex Relaxations and Applications

We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should a basis set of similarity functions be combined to induce NCuts favorable distributions. Such a procedure facilitates desig...

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Detalles Bibliográficos
Autores principales: Mukherjee, Lopamudra, Singh, Vikas, Peng, Jiming, Hinrichs, Chris
Formato: Artigo
Lenguaje:Inglês
Publicado: 2010
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Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC3063999/
https://ncbi.nlm.nih.gov/pubmed/21445225
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/CVPR.2010.5540076
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