Let D be a smoothly bounded pseudoconvex domain in c2. Let M be a one-dimensional subvariety of D which has no singularities on bM and intersects bD transversally. If bA4 consists of the points of finite type, then we can construct an integral kernel CM (C, z) for iM which satisfies the reproducing property of holomorphic functions f E O(A4) nC(a) from their boundary values. Furthermore, we get...

Maximum margin clustering (MMC) approaches extend the large margin principle of SVM to unsupervised learning with considerable success. In this work, we utilize the ratio between the margin and the intra-cluster variance, to explicitly consider both the separation and the compactness of the clusters in the objective. Moreover, we employ multiple kernel learning (MKL) to jointly learn the kernel...

Altering in-memory kernel data, attackers are able to manipulate the running behaviors of operating systems without injecting any malicious code. This type of attack is called kernel data attack. Intuitively, the security impact of such an attack seems minor, and thus, it has not yet drawn much attention from the security community. In this paper, we thoroughly investigate kernel data attack, s...