Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-labe...
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
It has long been noted that many data mining algorithms can be built on top of join algorithms. This has lead to a wealth of recent work on efficiently supporting such joins with ...
Lexiang Ye, Xiaoyue Wang, Dragomir Yankov, Eamonn ...
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Network security has been a serious concern for many years. For example, firewalls often record thousands of exploit attempts on a daily basis. Network administrators could benefi...
Jian Zhang 0004, Phillip A. Porras, Johannes Ullri...