Index Terms
- Students training students: a peer training program that works
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Multi-label co-training
IJCAI'18: Proceedings of the 27th International Joint Conference on Artificial IntelligenceMulti-label learning aims at assigning a set of appropriate labels to multi-label samples. Although it has been successfully applied in various domains in recent years, most multi-label learning methods require sufficient labeled training samples, ...
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers
In many practical data mining applications, such as Web page classification, unlabeled training examples are readily available, but labeled ones are fairly expensive to obtain. Therefore, semi-supervised learning algorithms such as co-training have ...
Self-Training with Selection-by-Rejection
ICDM '12: Proceedings of the 2012 IEEE 12th International Conference on Data MiningPractical machine learning and data mining problems often face shortage of labeled training data. Self-training algorithms are among the earliest attempts of using unlabeled data to enhance learning. Traditional self-training algorithms label unlabeled ...
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