Seminar on Internet Technologies (Winter 2017/2018): Difference between revisions

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| [http://ieeexplore.ieee.org/abstract/document/6847217/]
| [http://ieeexplore.ieee.org/abstract/document/6847217/]
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| '''A Survey on Semi-Supervised Learning Techniques'''
| '''A Survey on Semi-Supervised Learning Techniques (Assigned to Yifan Chen)'''
Semisupervised learning is a learning standard which deals with the study of how computers and natural systems such as human beings acquire knowledge in the presence of both labeled and unlabeled data. Semisupervised learning based methods are preferred when compared to the supervised and unsupervised learning because of the improved performance shown by the semisupervised approaches in the presence of large volumes of data. Labels are very hard to attain while unlabeled data are surplus, therefore semisupervised learning is a noble indication to shrink human labor and improve accuracy. In this work, this task is to survey some of the key approaches for semi-supervised learning. Note that this topic requires a comparatively high reading effort.
Semisupervised learning is a learning standard which deals with the study of how computers and natural systems such as human beings acquire knowledge in the presence of both labeled and unlabeled data. Semisupervised learning based methods are preferred when compared to the supervised and unsupervised learning because of the improved performance shown by the semisupervised approaches in the presence of large volumes of data. Labels are very hard to attain while unlabeled data are surplus, therefore semisupervised learning is a noble indication to shrink human labor and improve accuracy. In this work, this task is to survey some of the key approaches for semi-supervised learning. Note that this topic requires a comparatively high reading effort.
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
| [http://www.net.informatik.uni-goettingen.de/people/tao_zhao Tao Zhao]
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