Cargando…
Choosing ℓ(p) norms in high-dimensional spaces based on hub analysis
The hubness phenomenon is a recently discovered aspect of the curse of dimensionality. Hub objects have a small distance to an exceptionally large number of data points while anti-hubs lie far from all other data points. A closely related problem is the concentration of distances in high-dimensional...
Autores principales: | Flexer, Arthur, Schnitzer, Dominik |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science Publishers
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4567076/ https://www.ncbi.nlm.nih.gov/pubmed/26640321 http://dx.doi.org/10.1016/j.neucom.2014.11.084 |
Ejemplares similares
-
A comprehensive empirical comparison of hubness reduction in high-dimensional spaces
por: Feldbauer, Roman, et al.
Publicado: (2018) -
Asymptotic theory of finite dimensional normed spaces
por: Milman, Vitali D, et al.
Publicado: (1986) -
Mixed-norm inequalities and operator space L_{p} embedding theory
por: Junge, Marius, et al.
Publicado: (2010) -
Functional analysis in normed spaces
por: Kantorovich, Leonid Vitalievich, et al.
Publicado: (1964) -
Topology and normed spaces
por: Jameson, G. J. O. (Graham James Oscar)
Publicado: (1974)