Semi-supervised learning by disagreement |
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Authors: | Zhi-Hua Zhou Ming Li |
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Affiliation: | 1. National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210093, China
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Abstract: | In many real-world tasks, there are abundant unlabeled examples but the number of labeled training examples is limited, because labeling the examples requires human efforts and expertise. So, semi-supervised learning which tries to exploit unlabeled examples to improve learning performance has become a hot topic. Disagreement-based semi-supervised learning is an interesting paradigm, where multiple learners are trained for the task and the disagreements among the learners are exploited during the semi-supervised learning process. This survey article provides an introduction to research advances in this paradigm. |
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