Qingzhi Chen

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Kernel dependency estimation (KDE) is a learning framework of finding the dependencies between two general classes of objects. Although it has been successfully used for many types of applications, its properties are not fully studied. In this paper, we discuss two practical issues with KDE. The first one is its real-value output for each label, which(More)
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