Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
This is a summary of the main results presented in the author's PhD thesis, supervised by D. Conforti and P. Beraldi and defended on March 2005. The thesis, written in English...
We study upper and lower bounds on the kernel size for the 3-hitting set problem on hypergraphs of degree at most 3, denoted 33-hs. We first show that, unless P=NP, 3-3-hs on 3-un...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...