Manifold Regularized Multitask Learning for Semi-Supervised Multilabel Image Classification

DOI10.1109/TIP.2012.2218825zbMath1373.94269OpenAlexW1985583020WikidataQ42669030 ScholiaQ42669030MaRDI QIDQ5373209

Bo Geng, Chao Xu, Stephen J. Maybank, Yong Luo, Dacheng Tao

Publication date: 27 October 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tip.2012.2218825

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Image analysis in multivariate analysis (62H35) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (7)

Multiview sample classification algorithm based on L1-graph domain adaptation learning ⋮ Clustering of multivariate binary data with dimension reduction via \(L_{1}\)-regularized likelihood maximization ⋮ Manifold regularized matrix completion for multi-label learning with ADMM ⋮ Flexible multi-view semi-supervised learning with unified graph ⋮ Semi-supervised learning with local and global consistency ⋮ A multikernel-like learning algorithm based on data probability distribution ⋮ A multiple attributes convolution kernel with reproducing property

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