The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
Time series motifs are approximately repeated patterns found within the data. Such motifs have utility for many data mining algorithms, including rule-discovery, novelty-detection...
Dragomir Yankov, Eamonn J. Keogh, Jose Medina, Bil...
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
We focus on large graphs where nodes have attributes, such as a social network where the nodes are labelled with each person's job title. In such a setting, we want to find s...
Hanghang Tong, Christos Faloutsos, Brian Gallagher...
The proliferation of malware has presented a serious threat to the security of computer systems. Traditional signature-based antivirus systems fail to detect polymorphic and new, ...
We consider the problem of detecting anomalies in high arity categorical datasets. In most applications, anomalies are defined as data points that are 'abnormal'. Quite ...