Cargando…
Online Coregularization for Multiview Semisupervised Learning
We propose a novel online coregularization framework for multiview semisupervised learning based on the notion of duality in constrained optimization. Using the weak duality theorem, we reduce the online coregularization to the task of increasing the dual function. We demonstrate that the existing o...
Autores principales: | Sun, Boliang, Li, Guohui, Jia, Li, Huang, Kuihua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3782153/ https://www.ncbi.nlm.nih.gov/pubmed/24194680 http://dx.doi.org/10.1155/2013/398146 |
Ejemplares similares
-
Generalization Bounds for Coregularized Multiple Kernel Learning
por: Wu, Xinxing, et al.
Publicado: (2018) -
Self-Trained LMT for Semisupervised Learning
por: Fazakis, Nikos, et al.
Publicado: (2016) -
Cooperative learning for multiview analysis
por: Ding, Daisy Yi, et al.
Publicado: (2022) -
Semisupervised Semantic Segmentation with Mutual Correction Learning
por: Xiao, Yifan, et al.
Publicado: (2022) -
Multiview machine learning for data analysis
por: Sun, Shiliang, et al.
Publicado: (2019)