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Boosting is a very successful classification algorithm that produces a linear combination of "weak" classifiers (a.k.a. base learners) to obtain high quality classification models. In this paper we propose a new boosting algorithm where base learners have structure relationships in the functional space. Though such relationships are generic, our work is(More)
Determining anomalies in data streams that are collected and transformed from various types of networks has recently attracted significant research interest. Principal Component Analysis (PCA) has been extensively applied to detecting anomalies in network data streams. However, none of existing PCA based approaches addresses the problem of identifying the(More)
—Determining anomalies in data streams that are collected and transformed from various types of networks has recently attracted significant research interest. Principal Component Analysis (PCA) has been extensively applied to detecting anomalies in network data streams. However, none of existing PCA based approaches addresses the problem of identifying the(More)
Multi-task learning (MTL) aims to enhance the generalization performance of supervised regression or classification by learning multiple related tasks simultaneously. In this paper, we aim to extend the current MTL techniques to high dimensional data sets with structured input and structured output (SISO), where the SI means the input features are(More)
Information Flow Studies analyze the principles and mechanisms of social information distribution and is an essential research topic in social networks. Traditional approaches are primarily based on the social network graph topology. However, topology itself can not accurately reflect the user interests or activities. In this paper, we adopt a(More)
Principal Component Analysis based anomaly detection approaches have been extensively studied recently. However, none of these approaches address the problem of anomaly localization. In this paper, we proposed a novel approach based on PCA to perform anomaly detection and localiza-tion in sensor networks simultaneously. By enforcing the joint sparsity(More)