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Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning
(2012-12-01)
Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate ...
Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning
(2012-12-01)
Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(IEEE COMPUTER SOCLOS ALAMITOS, 2012)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(Institute of Electrical and Electronics Engineers (IEEE), Computer Soc, 2012-09-01)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
Particle Competition and Cooperation in Networks for Semi-Supervised Learning
(Institute of Electrical and Electronics Engineers (IEEE), Computer Soc, 2012-09-01)
Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) ...
Particle competition and cooperation for semi-supervised learning with label noise
(Elsevier B.V., 2015)
Semi-supervised learning for relevance feedback on image retrieval tasks
(Ieee, 2014-01-01)
Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts ...
Multi-label semi-supervised classification through optimum-path forest
(Elsevier B.V., 2018-10-01)
Multi-label classification consists of assigning one or multiple classes to each sample in a given dataset. However, the project of a multi-label classifier is usually limited to a small number of supervised samples as ...