Multi-label learning with co-training based on semi-supervised regression

Abstract

The goal of this paper is to categorize images with multiple labels based on semi-supervised learning. Conventional semi-supervised regression methods are predominantly used to solve single label problems. However, it is more common in many real-world practical applications that an instance can be associated with a set of labels simultaneously. In this… (More)
DOI: 10.1109/SPAC.2014.6982681

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@article{Xu2014MultilabelLW, title={Multi-label learning with co-training based on semi-supervised regression}, author={Meixiang Xu and Fuming Sun and Xiaojun Jiang}, journal={Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)}, year={2014}, pages={175-180} }