Hao-Heng Chien

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The Support Vector Machines (SVMs) have been widely used for classification due to its ability to give low generalization error. In many practical applications of classification, however, the wrong prediction of a certain class is much severer than that of the other classes, making the original SVM unsatisfactory. In this paper, we propose the notion of(More)
We study the target node prediction problem: given two social networks, identify those nodes/users from one network (called the source network) who are likely to join another (called the target network, with nodes called target nodes). Although this problem can be solved using existing techniques in the field of cross domain classification, we observe that(More)
The objective function of CICF, with the non-negative constraints on V and E, is a special case of Non-negative Matrix Factorization (NMF) (Lee & Seung, 1999; Recht et al., 2012; Seung & Lee, 2001; Yang et al., 2012), and can be solved by a multiplicative update approach (Seung & Lee, 2001; Yang & Oja, 2010). However, this approach suffers from the(More)
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