方法证据记录
Self-supervised Boosting
Self-supervised boosting integrates self-supervised pretext tasks into the boosting framework — covering AdaBoost, gradient boosting, and their modern variants — to leverage large pools of unlabeled data. By first learning feature representations from unlabeled samples and then running sequential weak-learner ensembles on pseudo-labeled data, it achieves competitive accuracy even when ground-truth labels are scarce.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Self-supervised Boosting (SSL-Boosting)
分类方法记录 · ml-model / machine-learning
- Yarowsky, D. (1995). Unsupervised word sense disambiguation rivaling supervised methods. In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (pp. 189–196). ACL. · URL
- Self-supervised learning. Wikipedia. · URL
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