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In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. It combines two desirable properties; firstly, a very small ...
... semi-supervised learning, obtaining generally comparable or better results. Keywords: Semi-supervised, Probabilistic Relaxation, Classification. 1 Introduction.
In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. It combines two desirable properties; firstly, ...
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... semi-supervised learning using the probabilistic relaxation theory. This technique uses contextual information for multi-class assignment of labels. Show ...
In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. It combines two desirable properties; firstly, a very small ...
This paper proposes a semi-supervised approach based on probabilistic relaxation theory. The algorithm performs a consistent multi-class assignment of ...
Missing: Classification | Show results with:Classification
Consequently, semi-supervised learning, which uses both labeled and ... and linear programming relaxation [28]. We follow the ICM ap- proach, which is ...
Jun 8, 2011 · PDF | In this paper, a semi-supervised approach based on probabilistic relaxation theory is presented. Focused on image segmentation, ...
Apr 5, 2024 · This thesis studies advanced probabilistic models, including both their theoretical foundations and practical applications, for different semi-supervised ...
Missing: Relaxation. | Show results with:Relaxation.
A multi-class semi-supervised learning algorithm based on probabilistic relaxation, which allows context information to be introduced into the system. The ...