Hessian-regularized co-training for social activity recognition.
Co-training is a major multi-view learning paradigm that alternately trains two classifiers on two distinct views and maximizes the mutual agreement on the two-view unlabeled data. Traditional co-training algorithms usually train a learner on each view separately and then force the learners to be co...
Main Authors: | Weifeng Liu, Yang Li, Xu Lin, Dacheng Tao, Yanjiang Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4178174?pdf=render |
Similar Items
-
Hessian-regularized weighted multi-view canonical correlation analysis for working condition recognition of sucker-rod pumping wells
by: Bin Zhou, et al.
Published: (2018-09-01) -
Scene categorization by Hessian-regularized active perceptual feature selection
by: Junwu Zhou, et al.
Published: (2025-01-01) -
Generalized Hessian-Schatten Norm Regularization for Image Reconstruction
by: Manu Ghulyani, et al.
Published: (2022-01-01) -
Delaunay-Triangulation-Based Learning With Hessian Total-Variation Regularization
by: Mehrsa Pourya, et al.
Published: (2023-01-01) -
Regularity of degenerate k-Hessian equations on closed Hermitian manifolds
by: Zhang Dekai
Published: (2022-10-01)