In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
Seung-Jean Kim, Alessandro Magnani, Stephen P. Boy...
Finding a constraint network that will be efficiently solved by a constraint solver requires a strong expertise in Constraint Programming. Hence, there is an increasing interest i...
We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
We consider kernel density estimation when the observations are contaminated by measurement errors. It is well known that the success of kernel estimators depends heavily on the c...
Abstract. The Still-Life problem is challenging for CP techniques because the basic constraints of the game of Life are loose and give poor propagation for Still-Life. In this pape...