Cargando…
Fundamental limits in structured principal component analysis and how to reach them
How do statistical dependencies in measurement noise influence high-dimensional inference? To answer this, we study the paradigmatic spiked matrix model of principal components analysis (PCA), where a rank-one matrix is corrupted by additive noise. We go beyond the usual independence assumption on t...
Autores principales: | Barbier, Jean, Camilli, Francesco, Mondelli, Marco, Sáenz, Manuel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374165/ https://www.ncbi.nlm.nih.gov/pubmed/37463204 http://dx.doi.org/10.1073/pnas.2302028120 |
Ejemplares similares
-
Breeding Schemes: What Are They, How to Formalize Them, and How to Improve Them?
por: Covarrubias-Pazaran, Giovanny, et al.
Publicado: (2022) -
Principal component analysis is limited to low-resolution analysis in cryoEM
por: Sorzano, Carlos Oscar S., et al.
Publicado: (2021) -
Limitations of principal components in quantitative genetic association models for human studies
por: Yao, Yiqi, et al.
Publicado: (2023) -
Have the “mega-journals” reached the limits to growth?
por: Björk, Bo-Christer
Publicado: (2015) -
How European physics reached across the Wall
por: Stange, T
Publicado: (2002)